Sample handling apparatus and image registration methods

ABSTRACT

A method for aligning a sample to an array is provided. An image of sample image of a sample can be received by a data processor. The sample image having a first resolution. An array image including an overlay of an array with the sample and an array fiducial can be received by the data processor. The array image having a second resolution lower than the first resolution of the sample image. The sample image can be registered to the array image by aligning the sample image and the array image. An aligned image can be generated based on the registering. The aligned image can can include an overlay of the sample image with the array. The aligned image can be provided by the data processor. A method for detecting fiducials associated with an array is provided. Systems and non-transitory computer readable mediums performing the method are also provided.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of and claims priority to WOApplication No. PCT/US2021/050929 filed on Sep. 17, 2021, which claimsthe benefit of U.S. Provisional Patent Application No. 63/080,547 filedSep. 18, 2020 and U.S. Provisional Patent Application No. 63/155,173filed Mar. 1, 2021, the contents of each of which are herebyincorporated by reference in their entirety.

BACKGROUND

Cells within a tissue of a subject have differences in cell morphologyand/or function due to varied analyte levels (e.g., gene and/or proteinexpression) within the different cells. The specific position of a cellwithin a tissue (e.g., the cell's position relative to neighboring cellsor the cell's position relative to the tissue microenvironment) canaffect, e.g., the cell's morphology, differentiation, fate, viability,proliferation, behavior, and signaling and cross-talk with other cellsin the tissue.

Spatial heterogeneity has been previously studied using techniques thatonly provide data for a small handful of analytes in the context of anintact tissue or a portion of a tissue, or provide a lot of analyte datafor single cells, but fail to provide information regarding the positionof the single cell in a parent biological sample (e.g., tissue sample).

Analytes from a biological sample can be captured onto a reagent arraywhile preserving spatial context of the analytes. The captured analytescan be used to generate a sequence data that can be mapped to an imageof the biological sample. There exists a need for improved methods andsystems for registering the image data with the sequence data.

Image data can be utilized to assess the spatial heterogeneity ofanalyte levels for cells and tissues. To accurately determine the degreeof spatial heterogeneity and transcriptomic activity within a cell ortissue, image data associated with a sample of a cell or a tissue can bealigned with image data associated with a reagent array configured tocapture analytes from the cell or tissue sample. The alignment can bedetermined using image registration to provide accurate spatial mappingof the transcriptomic activity within a sample. Various methods ofperforming image registration on biological samples are describedherein.

SUMMARY

All publications, patents, patent applications, and informationavailable on the internet and mentioned in this specification are hereinincorporated by reference to the same extent as if each individualpublication, patent, patent application, or item of information wasspecifically and individually indicated to be incorporated by reference.To the extent publications, patents, patent applications, and items ofinformation incorporated by reference contradict the disclosurecontained in the specification, the specification is intended tosupersede and/or take precedence over any such contradictory material.

Analytes within a biological sample are generally released throughdisruption (e.g., permeabilization) of the biological sample. Variousmethods of disrupting a biological sample are known, includingpermeabilization of the cell membrane of the biological sample.Described herein are methods of delivering a fluid to the biologicalsample, systems for sample analysis, and sample alignment methods.

In one aspect, a method for aligning a sample to an array is provided.The method includes receiving, by a data processor, sample image datacomprising a sample image of the sample. The sample image can have afirst resolution. The method further includes receiving, by the dataprocessor, array image data including an array image including anoverlay of an array with the sample and an array fiducial. The arrayimage can have a second resolution lower than the first resolution ofthe sample image. The method also includes registering, by the dataprocessor, the sample image to the array image by aligning the sampleimage and the array image. The method further includes generating, bythe data processor, an aligned image based on the registering. Thealigned image can include an overlay of the sample image with the array.The method also includes providing, by the data processor, the alignedimage.

In some variations, one or more features disclosed herein including thefollowing features may optionally be included in any feasiblecombination. For example, the sample image data can be received from auser or from a computing device remote from the data processor. Thealigned image can include the array fiducial aligned with the sample.The sample image can include a sample fiducial delineating a sample areainto which the sample is placed.

In some embodiments, the sample image can be of the sample on a firstsubstrate. In some embodiments, the sample can be located on a firstsubstrate and the array can be located on a second substrate. The arrayand the array fiducial can be located on a first side of a secondsubstrate. In some embodiments, the array fiducial can be located on thesecond substrate adjacent to, within, or distanced from a reagentconfigured on the second substrate. In some embodiments, the array imagecan include a portion of the array overlaid top a portion of the samplebased on allocation of the array fiducial.

In some embodiments, the sample image can include a plurality of sampleportion images and each sample portion image can be associated with aportion of the sample. In some embodiments, a size of each sampleportion image can be less than a size of a single field of view of thesample image.

In some embodiments, registering the sample image to the array image caninclude cropping, by the data processor, the sample image to determinethe plurality of sample portion images and registering one or moresample portion images in the sample image to a corresponding portion ofthe sample in the array image. In some embodiments, registering the oneor more sample portion images in the sample image to the correspondingportion of the sample in the array image can be performed afterregistering the sample image to the array image. In some embodiments,the array image can include a plurality of array portion images. Eacharray portion image can be associated with a portion of the array. Asize of each array portion image can be less than a size of a singlefield of view of the array image.

In some embodiments, the registering can include determining, by thedata processor, the plurality of array portion images in the array imageand registering, by the data processor, one or more array portion imagesin the array image to a corresponding portion of the sample in thesample image.

In another aspect, a system for aligning a sample to an array isprovided. The system can include a sample holder including a firstretaining mechanism configured to retain a first substrate within thefirst retaining mechanism. The first substrate can include a sample. Thesample holder can also include a second retaining mechanism configuredto retain a second substrate received within the second retainingmechanism. The second substrate can include an array. The sample holdercan be configured to adjust a location of the first substrate relativeto the second substrate to cause all or a portion of the sample to bealigned with the array. The system can further include a microscopeoperatively coupled to the sample holder. The microscope can beconfigured to view the first substrate and the second substrate withinthe sample holder and can acquire image data associated with the sampleand/or the array. The system can also include a first computing devicecommunicatively coupled to the microscope and to the sample holder. Thecomputing device can include a display, a data processor, and anon-transitory computer readable storage medium storing computerreadable and executable instructions, which when executed can cause thedata processor to perform operations including receiving sample imagedata comprising a sample image of the sample. The sample image can havea first resolution. The operations can also include receiving arrayimage data including an array image having a second resolution lowerthan the first resolution of the sample image. The array image caninclude the array and an array fiducial overlaid atop the sample. Theoperations can further include registering the sample image to the arrayimage by aligning the sample image and the array image. The operationscan also include generating an aligned image based on the registering.The aligned image can include the sample aligned with the array andproviding the aligned image.

In some variations, one or more features disclosed herein including thefollowing features may optionally be included in any feasiblecombination. For example, the sample image data can be received from auser or from a computing device remote from the data processor. Thealigned image can further include the array fiducial aligned with thesample. The sample image can further include a sample fiducialdelineating a sample area into which the sample can be placed on thefirst substrate. The sample image can be of the sample on the firstsubstrate.

The array fiducial can be located on the second substrate adjacent to,within, or distanced from a reagent configured on the second substrate.The sample image can include a plurality of sample portion images. Eachsample portion image can be associated with a portion of the sample. Asize of each sample portion image can be less than a size of a singlefield of view of the sample image.

In some embodiments, the registering can include cropping, by the dataprocessor, the sample image to determine the plurality of sample portionimages and registering one or more sample portion images in the sampleimage to a corresponding portion of the sample in the array image.

In some embodiments, the array image can include a plurality of arrayportion images. Each array portion image can be associated with aportion of the array. A size of each array portion image can be lessthan a size of a single field of view of the array image. In someembodiments, the registering can include determining the plurality ofarray portion images in the array image and registering one or morearray portion images in the array image to a corresponding portion ofthe sample in the sample image.

Where values are described in terms of ranges, it should be understoodthat the description includes the disclosure of all possible sub-rangeswithin such ranges, as well as specific numerical values that fallwithin such ranges irrespective of whether a specific numerical value orspecific sub-range is expressly stated.

The term “each,” when used in reference to a collection of items, isintended to identify an individual item in the collection but does notnecessarily refer to every item in the collection, unless expresslystated otherwise, or unless the context of the usage clearly indicatesotherwise.

Various embodiments of the features of this disclosure are describedherein. However, it should be understood that such embodiments areprovided merely by way of example, and numerous variations, changes, andsubstitutions can occur to those skilled in the art without departingfrom the scope of this disclosure. It should also be understood thatvarious alternatives to the specific embodiments described herein arealso within the scope of this disclosure.

DESCRIPTION OF DRAWINGS

The following drawings illustrate certain embodiments of the featuresand advantages of this disclosure. These embodiments are not intended tolimit the scope of the appended claims in any manner. Like referencesymbols in the drawings indicate like elements.

FIG. 1 shows an exemplary spatial analysis workflow in accordance withsome example implementations.

FIG. 2 depicts an example workflow for preparing the biological sampleon a slide in accordance with some example implementations.

FIG. 3 is a schematic diagram depicting an exemplary permeabilizationsolution interaction between a tissue slide and a gene expression slidein a sandwich configuration in accordance with some exampleimplementations.

FIG. 4 is a schematic diagram showing an example sample handlingapparatus in accordance with some example implementations.

FIG. 5A depicts an example first member and an example second member inaccordance with some example implementations.

FIG. 5B depicts an example of the first member coupled to the secondmember in accordance with some example implementations.

FIG. 5C depicts an example of the first member coupled to the secondmember including a coupling member coupled to the first substrate andthe second substrate in accordance with some example implementations.

FIG. 6 is a diagram of an example first member and an example secondmember in accordance with some example implementations.

FIG. 7 depicts a diagram of a close-up bottom view of the first membercoupled to the second member and an overlap area where the firstsubstrate overlaps with the second substrate in accordance with someexample implementations.

FIG. 8 depicts a front cross-sectional view of the example samplehandling apparatus in accordance with some example implementations.

FIG. 9 is diagram of an example adjustment mechanism in accordance withsome example implementations.

FIG. 10 is a perspective view of an example sample handling apparatusincluding an automated second member in accordance with some exampleimplementations.

FIG. 11A is a perspective view of an example sample handling apparatusincluding a heater in accordance with some example implementations.

FIG. 11B is a exploded view of an example second member including theheater in accordance with some example implementations.

FIG. 11C is a graph of an example desired substrate (e.g., slide)temperature profile over time in accordance with some exampleimplementations.

FIG. 12A is a perspective view of an example first member in accordancewith some example implementations.

FIG. 12B is an exploded view of the example first member of FIG. 12A inaccordance with some example implementations.

FIG. 13A is a perspective cross-section view of an example first memberin accordance with some example implementations.

FIG. 13B is a perspective view of the example holder plate of FIG. 13Ain accordance with some example implementations.

FIG. 13C is a perspective view of the example heat sink block of FIG.13A in accordance with some example implementations.

FIG. 14A is a perspective view of an example sample handling apparatusin a closed position in accordance with some example implementations.

FIG. 14B is a perspective view of the example sample handling apparatusin an open position in accordance with some example implementations.

FIG. 15 is a perspective view of the example sample handling apparatusin accordance with some example implementations.

FIG. 16A is a perspective view of the example sample handling apparatusin accordance with some example implementations.

FIG. 16B is a front view of the example sample handling apparatusshowing example dimensions of the apparatus in accordance with someexample implementations.

FIG. 16C is a side view of the example sample handling apparatus showingexample dimensions of the apparatus in accordance with some exampleimplementations.

FIGS. 17A-17C depict a workflow for loading slides into a samplehandling apparatus for later alignment in accordance with some exampleimplementations.

FIGS. 18A-18C depict a workflow for aligning the loaded slides of thesample handling apparatus in accordance with some exampleimplementations.

FIG. 19 is a process flow diagram illustrating an example process foraligning a sample area with an array area according to someimplementations of the current subject matter.

FIG. 20 depicts a workflow for adjusting a location of the firstsubstrate relative to the second substrate to align all or a portion ofa sample area with an array area according to some implementations ofthe current subject matter.

FIGS. 21A-21B depict a workflow for adjusting a location of the firstsubstrate relative to the second substrate based on an array areaindicator configured within a sample holder according to someimplementations of the current subject matter.

FIGS. 21C-21D depict a workflow for adjusting a location of multiplefirst substrates relative to the second substrate based on multiplearray area indicators configured within a sample holder according tosome implementations of the current subject matter.

FIGS. 22A-22C depicts a workflow for indicating a sample area of asubstrate according to some implementations of the current subjectmatter.

FIG. 23 is a process flow diagram illustrating an example process forautomatically determining a sample area indicator based on a receivedimage of the sample according to some implementations of the currentsubject matter.

FIGS. 24A-24B depict a workflow for receiving an input identifying asample area indicator based on an image of a sample.

FIG. 25 is a process flow diagram illustrating an example process forautomatically determining a sample area indicator based on a receivedplurality of video images according to some implementations of thecurrent subject matter.

FIG. 26 is a process flow diagram illustrating an example process forautomatically determining a sample area indicator responsive todetermining an area of the sample according to some implementations ofthe current subject matter.

FIG. 27 is a process flow diagram illustrating an example process fordetermining a fiducial mark located on a first substrate according tosome implementations of the current subject matter.

FIG. 28 is a process flow diagram illustrating an example process foridentifying the sample area indicator based on a registered sample imageaccording to some implementations of the current subject matter.

FIGS. 29A-29C depict a workflow for permeabilization of a sample of thesample handling apparatus in accordance with some exampleimplementations.

FIG. 30 is a diagram of an example sample handling apparatus inaccordance with some example implementations.

FIGS. 31A-31C depict a workflow for image capture of the sandwichedslides of the sample handling apparatus during a permeabilization stepin accordance with some example implementations.

FIG. 32 is a process flow diagram illustrating an example process forgenerating an aligned image based on registering a sample image to anarray image according to some implementations of the current subjectmatter.

FIGS. 33A-33E depict a workflow for registering a sample image to anarray image according to some implementations of the current subjectmatter.

FIGS. 34A-34E depict a workflow for registering a sample image to anarray image based on aligning a sample fiducial and an array fiducialaccording to some implementations of the current subject matter.

FIGS. 35A-35E depict a workflow for registering a sample image to anarray image based on aligning a user-provided sample fiducial and anarray fiducial according to some implementations of the current subjectmatter.

FIGS. 36A-36B depict a workflow for registering a sample image to anarray image based on aligning an edge of a sample substrate and an arrayfiducial according to some implementations of the current subjectmatter.

FIGS. 37A-37D are diagrams illustrating embodiments of sample fiducialsaccording to some implementations of the current subject matter.

FIGS. 38A-38C are diagrams illustrating embodiments of a sample fiducialconfigured on a rear of a sample substrate according to someimplementations of the current subject matter.

FIGS. 39A-39E are diagrams illustrating embodiments of configurations ofarray fiducials according to some implementations of the current subjectmatter.

FIGS. 40A-40C are diagrams illustrating embodiments of locations atwhich a low-resolution image including an array overlaid atop a samplecan be captured for registering a sample image to an array imageaccording to some implementations of the current subject matter.

FIG. 41 is a process flow diagram illustrating an example process forgenerating an aligned image based on registering a sample image to anarray image using multiple instrument fiducials according to someimplementations of the current subject matter.

FIGS. 42A-42D depict a workflow for generating an aligned image based onregistering a sample image to an array image using multiple instrumentfiducials according to some implementations of the current subjectmatter.

FIGS. 43A-43B illustrate stitching artifacts which can be present withinstitched images including a plurality of individual image portions.

FIG. 44 is a process flow diagram illustrating an example process forregistering sample portion images of a sample image to correspondingportions of the sample in an array image according to someimplementations of the current subject matter.

FIG. 45 depicts a workflow for registering sample portion images of asample image to corresponding portions of the sample in an array imageaccording to some implementations of the current subject matter.

FIG. 46 is a process flow diagram illustrating an example process forregistering array portion images of an array image to correspondingportions of the sample in a sample image according to someimplementations of the current subject matter.

FIG. 47 depicts a workflow for registering array portion images of anarray image to corresponding portions of the sample in a sample imageaccording to some implementations of the current subject matter.

FIG. 48 is a process flow diagram illustrating an example process forregistering stitched sample portion images to corresponding portions ofthe sample in a sample image according to some implementations of thecurrent subject matter.

FIG. 49 is a process flow diagram illustrating an example process forregistering stitched sample portion images to corresponding portions ofthe sample in a sample image based on determining one or more barcodedlocations of an array in according to some implementations of thecurrent subject matter.

FIG. 50 depicts a workflow for registering stitched sample portionimages to corresponding portions of the sample in a sample imageaccording to some implementations of the current subject matter.

FIG. 51 is a process flow diagram illustrating an example process forregistering stitched sample portion images to corresponding portions ofthe sample in a sample image and registering stitched array portionimages to corresponding portions of the sample in the sample imageaccording to some implementations of the current subject matter.

FIG. 52 depicts a workflow for registering stitched sample portionimages to corresponding portions of the sample in a sample image andregistering stitched array portion images to corresponding portions ofthe sample in the sample image according to some implementations of thecurrent subject matter.

FIG. 53 is a diagram of an example system architecture for performingthe image registration processes and workflows described herein inaccordance with some example implementations.

FIG. 54 is a diagram of an example software architecture for performingthe processes and workflows described herein in accordance with someexample implementations.

FIG. 55 is a diagram of an example architecture of the image managementsubsystem shown in FIG. 54 in accordance with some exampleimplementations.

FIG. 56 is a diagram illustrating an example architecture of a computingdevice in accordance with some example implementations.

FIG. 57 is an example interface display provided by the visualizationtools described herein in accordance with some example implementations.

FIGS. 58A-58B depict a configuration of a sample and an array in whicharray fiducials are not overlapped with the sample in acquired imagedata in accordance with some example implementations.

FIG. 59 is a process flow diagram illustrating an example process fordetecting fiducials associated with an array in accordance with someexample implementations.

FIGS. 60A-60B depict a workflow for detecting array fiducials overlappedwith a sample in acquired image data in accordance with some exampleimplementations.

FIGS. 61A-61B depict a workflow for detecting array fiducials overlappedwith a sample in image data acquired at different focal planes inaccordance with some example implementations.

FIGS. 62A-62B depict a workflow for detecting array fiducials overlappedwith a sample in image data acquired at different illuminations inaccordance with some example implementations.

FIGS. 63A-63B are images illustrating image data acquired at differentilluminations in accordance with some example implementations.

FIG. 64 is a process flow diagram illustrating an example process fordetecting fiducials associated with an array using instrument fiducialsprovided in a sample handling apparatus in accordance with some exampleimplementations.

FIGS. 65A-65B depict a workflow for detecting array fiducials overlappedwith a sample in image data including instrument fiducials provided in asample handling apparatus in accordance with some exampleimplementations.

FIG. 66 is a process flow diagram illustrating an example process fordetecting fiducials applied to a substrate on which an array is locatedin accordance with some example implementations.

FIGS. 67A-67B depict a workflow for detecting array fiducials overlappedwith a sample in image data including fiducials applied to a substrateon which an array is located in accordance with some exampleimplementations.

FIGS. 68A-68B depict a workflow for detecting array fiducials overlappedwith a sample in image data acquired in relation to a permeabilizationof the sample in accordance with some example implementations.

FIG. 69 is a process flow diagram illustrating an example process fordetecting fiducials using image registration of sample image data andarray image data acquired in a sample handling apparatus includingspacers configured on an array substrate in accordance with some exampleimplementations.

FIGS. 70A-70B depict a workflow for detecting array fiducials overlappedwith a sample in image data acquired and registered using a samplehandling apparatus including spacers in accordance with some exampleimplementations.

FIG. 71 is a process flow diagram illustrating an example process fordetecting fiducials using image registration of sample image data andarray image data acquired at multiple illuminations in a sample handlingapparatus including spacers in accordance with some exampleimplementations.

FIGS. 72A-72B depict a workflow for detecting array fiducials overlappedwith a sample in image data acquired and registered at multipleilluminations using a sample handling apparatus including spacers inaccordance with some example implementations.

FIGS. 73A-73C are images illustrating embodiments of image data acquiredat different illuminations by a sample handling apparatus for use inimage registration processes and techniques according to some exampleimplementations.

FIGS. 74A-74B are images illustrating additional embodiments of imagedata acquired at different illuminations by a sample handling apparatusfor use in image registration processes and techniques according to someexample implementations.

FIGS. 75A-75D are plots illustrating example data associated withregistration and position errors used in verifying the imageregistration processes and techniques described herein according to someexample implementations.

FIG. 76 depicts an exemplary workflow for image and video capture by asample handling apparatus described herein according to some exampleimplementations.

DETAILED DESCRIPTION I. Introduction

This disclosure describes apparatus, systems, methods, and compositionsfor spatial analysis of biological samples. This section describescertain general terminology, analytes, sample types, and preparativesteps that are referred to in later sections of the disclosure. Forexample, the terms and phrases: spatial analysis, barcode, nucleic acid,nucleotide, probe, target, oligonucleotide, polynucleotide, subject,genome, adaptor, adapter, tag, hybridizing, hybridize, annealing,anneal, primer, primer extension, proximity ligation, nucleic acidextension, polymerase chain reaction (PCR) amplification, antibody,affinity group, label, detectable label, optical label, templateswitching oligonucleotide, splint oligonucleotide, analytes, biologicalsamples, general spatial array-based analytical methodology, spatialanalysis methods, immunohistochemistry and immunofluorescence, captureprobes, substrates, arrays, analyte capture, partitioning, analysis ofcaptured analytes, quality control, multiplexing, and/or the like aredescribed in more detail in PCT Patent Application Publication No.WO2020/123320, the entire contents of which are incorporated herein byreference.

Tissues and cells can be obtained from any source. For example, tissuesand cells can be obtained from single-cell or multicellular organisms(e.g., a mammal). The relationship between cells and their relativelocations within a tissue sample may be critical to understandingdisease pathology. Spatialomic (e.g., spatial transcriptomic) technologymay allow scientists to measure all the gene activity in a tissue sampleand map where the activity is occurring. This technology and embodimentsdescribed herein may lead to new discoveries that may prove instrumentalin helping scientists gain a better understanding of biologicalprocesses and disease.

Tissues and cells obtained from a mammal, e.g., a human, often havevaried analyte levels (e.g., gene and/or protein expression) which canresult in differences in cell morphology and/or function. The positionof a cell or a subset of cells (e.g., neighboring cells and/ornon-neighboring cells) within a tissue can affect, e.g., the cell'sfate, behavior, morphology, and signaling and cross-talk with othercells in the tissue. Information regarding the differences in analytelevels (gene and/or protein expression) within different cells in atissue of a mammal can also help physicians select or administer atreatment that will be effective and can allow researchers to identifyand elucidate differences in cell morphology and/or cell function in thesingle-cell or multicellular organisms (e.g., a mammal) based on thedetected differences in analyte levels within different cells in thetissue. Differences in analyte levels within different cells in a tissueof a mammal can also provide information on how tissues (e.g., healthyand diseased tissues) function and/or develop. Differences in analytelevels within different cells in a tissue of a mammal can also provideinformation of different mechanisms of disease pathogenesis in a tissueand mechanism of action of a therapeutic treatment within a tissue.

The spatial analysis methodologies herein provide for the detection ofdifferences in an analyte level (e.g., gene and/or protein expression)within different cells in a tissue of a mammal or within a single cellfrom a mammal. For example, spatial analysis methodologies can be usedto detect the differences in analyte levels (e.g., gene and/or proteinexpression) within different cells in histological slide samples, thedata from which can be reassembled to generate a three-dimensional mapof analyte levels (e.g., gene and/or protein expression) of a tissuesample obtained from a mammal, e.g., with a degree of spatial resolution(e.g., single-cell resolution).

Spatial heterogeneity in developing systems has typically been studiedvia RNA hybridization, immunohistochemistry, fluorescent reporters, orpurification or induction of pre-defined subpopulations and subsequentgenomic profiling (e.g., RNA-seq). Such approaches, however, rely on arelatively small set of pre-defined markers, therefore introducingselection bias that limits discovery. These prior approaches also relyon a priori knowledge. RNA assays traditionally relied on staining for alimited number of RNA species. In contrast, single-cell RNA-sequencingallows for deep profiling of cellular gene expression (includingnon-coding RNA), but the established methods separate cells from theirnative spatial context.

Spatial analysis methodologies described herein provide a vast amount ofanalyte level and/or expression data for a variety of multiple analyteswithin a sample at high spatial resolution, e.g., while retaining thenative spatial context.

The binding of an analyte to a capture probe can be detected using anumber of different methods, e.g., nucleic acid sequencing, fluorophoredetection, nucleic acid amplification, detection of nucleic acidligation, and/or detection of nucleic acid cleavage products. In someexamples, the detection is used to associate a specific spatial barcodewith a specific analyte produced by and/or present in a cell (e.g., amammalian cell).

Capture probes can be, e.g., attached to a surface, e.g., a solid array,a bead, or a coverslip. In some examples, capture probes are notattached to a surface. In some examples, capture probes can beencapsulated within, embedded within, or layered on a surface of apermeable composition (e.g., any of the substrates described herein).

Non-limiting aspects of spatial analysis methodologies are described inWO 2011/127099, WO 2014/210233, WO 2014/210225, WO 2016/162309, WO2018/091676, WO 2012/140224, WO 2014/060483, U.S. Pat. Nos. 10,002,316,9,727,810, U.S. Patent Application Publication No. 2017/0016053,Rodrigues et al., Science 363(6434):1463-1467, 2019; WO 2018/045186, Leeet al., Nat. Protoc. 10(3):442-458, 2015; WO 2016/007839, WO2018/045181, WO 2014/163886, Trejo et al., PLoS ONE 14(2):e0212031,2019, U.S. Patent Application Publication No. 2018/0245142, Chen et al.,Science 348(6233):aaa6090, 2015, Gao et al., BMC Biol. 15:50, 2017, WO2017/144338, WO 2018/107054, WO 2017/222453, WO 2019/068880, WO2011/094669, U.S. Pat. Nos. 7,709,198, 8,604,182, 8,951,726, 9,783,841,10,041,949, WO 2016/057552, WO 2017/147483, WO 2018/022809, WO2016/166128, WO 2017/027367, WO 2017/027368, WO 2018/136856, WO2019/075091, U.S. Pat. No. 10,059,990, WO 2018/057999, WO 2015/161173,and Gupta et al., Nature Biotechnol. 36:1197-1202, 2018, the entirecontents of which are incorporated herein by reference and can be usedherein in any combination. Further non-limiting aspects of spatialanalysis methodologies are described herein.

Embodiments described herein may map the spatial gene expression ofcomplex tissue samples (e.g., on tissue slides) with slides (e.g., geneexpression slides) that utilize analyte and/or mRNA transcript captureand spatial barcoding technology for library preparation. A tissue(e.g., fresh-frozen, formalin fixed paraffin-embedded (FFPE), or thelike may be sectioned and placed in proximity to a slide with thousandsof barcoded spots, each containing millions of capture oligonucleotideswith spatial barcodes unique to that spot. Once tissue sections arefixed, stained, and permeabilized, they release mRNA which binds tocapture oligos from a proximal location on the tissue. A reversetranscription reaction may occur while the tissue is still in place,generating a cDNA library that incorporates the spatial barcodes andpreserves spatial information. Barcoded cDNA libraries are mapped backto a specific spot on a capture area of the barcoded spots. This geneexpression data may be subsequently layered over a high-resolutionmicroscope image of the tissue section, making it possible to visualizethe expression of any mRNA, or combination of mRNAs, within themorphology of the tissue in a spatially-resolved manner.

FIG. 1 shows an exemplary spatial analysis workflow 100 in accordancewith some example implementations. The workflow 100 includes preparing abiological sample on a slide (e.g., a pathology slide) 101, fixing thesample, and/or staining 102 the biological sample for imaging. Thestained sample can be then imaged on the slide using brightfield (toimage the sample hematoxylin and eosin stain) and/or fluorescence (toimage features) modalities. The imaging may include high-resolutionimaging (e.g., images that can disclose pathological and histologicalfeatures). Optionally, at 103, the sample can be destained prior topermeabilization. At 104, a permeabilization solution may be applied tobiological sample while the pathology slide is aligned in a “sandwich”configuration with a slide comprising a spatially barcoded array (e.g.,on an array slide). The permeabilization solution allowing the analyteand/or mRNA transcripts to migrate away from the sample, diffuse acrossthe permeabilization solution, and toward the array. The analyte and/ormRNA transcripts interacts with a capture probe on the slide.

At 105, the capture probes can be optionally cleaved from the array, andthe captured analytes can be spatially-barcoded by performing a reversetranscriptase first strand cDNA reaction. A first strand cDNA reactioncan be optionally performed using template switching oligonucleotides.At 106, the first strand cDNA can be amplified (e.g., using polymerasechain reaction (PCR)), where the forward and reverse primers flank thespatial barcode and analyte regions of interest, generating a libraryassociated with a particular spatial barcode. In some embodiments, thecDNA comprises a sequencing by synthesis (SBS) primer sequence. Thelibrary amplicons may be sequenced and analyzed to decode spatialinformation.

FIG. 2 depicts an example workflow 101 for preparing the biologicalsample on the slide (e.g., a pathology slide) in accordance with someexample implementations. Preparing the biological sample on the slidemay include selecting a pathology glass slide 201. The workflow 101further includes placing tissue sections on the glass slide 202. Placingtissue sections on the glass slide may include placing the tissueanywhere on the glass slide including placing the tissue on or inrelation to a fiducial disposed on the glass slide. The fiducial mayinclude any marking to aid in placement of the tissue on the slideand/or aid in the alignment of the tissue slide relative to the geneexpression slide. The workflow 101 further includes staining the tissuewith hematoxylin and eosin 203 or another staining agent or method. Theworkflow 101 further includes imaging the tissue 204 on the slide usingbrightfield (e.g., to image the sample hematoxylin and eosin stain) oranother imaging technique. The imaging may include high-resolutionimaging on a user imaging system. The imaging may also include imagingperformed using an image capture device configured in the samplehandling apparatuses described herein. In some embodiments, the imagingperformed using the image capture device can include low-resolution orhigh-resolution imaging. The imaging may allow the user to confirm therelevant pathology and/or identify any target areas for analysis. Theimaging can be performed in one or more image capture modes using theimage capture device and sample handling apparatus described herein.

Embodiments described herein relating to preparing the biological sampleon the slide may beneficially allow a user to confirm pathology orrelevant regions on a tissue section, to confirm selection of best orundamaged tissue sections for analysis, to improve array-tissuealignment by allowing placement anywhere on the pathology slide.Further, workflows for preparing the biological sample on the slide mayempower user or scientists to choose what to sequence (e.g., what tissuesection(s) to sequence).

FIG. 3 is a schematic diagram depicting an exemplary sandwiching process(e.g., permeabilization solution interaction) 104 between a firstsubstrate comprising a biological sample such as a tissue section (e.g.,a tissue slide) and a second substrate comprising a spatially barcodedarray, (e.g., a gene expression slide) in a sandwich configuration inaccordance with some example implementations. During an exemplarysandwiching process, the first substrate is aligned with the secondsubstrate, such that at least a portion of the biological sample isaligned with at least a portion of the array (e.g., aligned in asandwich configuration). In the exemplary configuration, a sample (atissue or biological sample) 302 is disposed on the pathology slide 303and is sandwiched between the pathology slide 303 and a slide 304 (e.g.,gene expression slide) that is populated with spatially-barcoded captureprobes 306. As shown, the slide 304 is in a superior position to thepathology slide 303. In some embodiments, the pathology slide 303 may bepositioned superior to the glass slide 304. When a permeabilizationsolution 305 is applied to a gap 307 between the pathology slide 303 andthe slide 304, the permeabilization solution 305 creates apermeabilization buffer which permeabilizes or digests the sample 302and the analytes (e.g., mRNA transcripts) 308 of the tissue sample 302may release, diffuse across the gap 307 toward the capture probes 306,and bind on the capture probes 306. In some embodiments, analyte captureagents that have bound to analytes in the sample (or portions of suchanalyte capture agents) may release, actively or passively migrateacross the gap and bind on the capture probes.

After the analytes (e.g., transcripts) 308 bind on the capture probes306, an extension reaction (e.g., a reverse transcription reaction) mayoccur, generating a spatially barcoded library. For example, in the caseof mRNA transcripts, reverse transcription may occur, thereby generatinga cDNA library associated with a particular spatial barcode. BarcodedcDNA libraries may be mapped back to a specific spot on a capture areaof the capture probes 306. This gene expression data may be subsequentlylayered over a high-resolution microscope image of the tissue section((e.g., taken at 204 of FIG. 2 ), making it possible to visualize theexpression of any mRNA, or combination of mRNAs, within the morphologyof the tissue in a spatially-resolved manner.

In some embodiments, the extension reaction can be performed separatelyfrom the sample handling apparatus described herein that is configuredto perform the exemplary sandwiching process 104. The sandwichconfiguration of the sample 302, the pathology slide 303 and the slide304 may provide advantages over other methods of spatial analysis and/oranalyte capture. For example, the sandwich configuration may reduce aburden of users to develop in house tissue sectioning and/or tissuemounting expertise. Further, the sandwich configuration may decouplesample preparation/tissue imaging from the barcoded array (e.g.,spatially-barcoded capture probes 306) and enable selection of aparticular region of interest of analysis (e.g., for a tissue sectionlarger than the barcoded array). The sandwich configuration alsobeneficially enables spatial analysis without having to place a tissuesection 302 directly on the gene expression slide (e.g., slide 304).

The sandwich configuration described herein further provides thebeneficial ability to quality check or select specific sections oftissue prior to committing additional time and resources to the analysisworkflow. This can be advantageous to reduce costs and risk or mistakesor issues that can arise during sample preparation. Additionally, thesandwich configuration can enable the ability to select which area of asample to sequence when a sample section is larger than an array.Another benefit of using the sandwich configuration described herein isthe ability to separate fiducial imaging and high-resolution sampleimaging. This can enable the separation of expertise required to performhistology workflows and molecular biology workflows and can furtherenable the assay and the sample to be moved between differentlaboratories. Additionally, the sandwich configuration described hereincan provide great flexibility and more options in sample preparationconditions since there are no oligos on the sample substrate or slide.This can reduce the likelihood a sample may fall off the substrate andcan reduce the likelihood that oligos are damaged due to hightemperatures or interactions with other reagents during samplepreparation. The sandwich configuration described herein can alsoimprove the sensitivity and spatial resolution by vertically confiningtarget molecules within the diffusion distance.

II. Systems for Sample Analysis

The methods described above for analyzing biological samples, such asthe sandwich configuration described above, can be implemented using avariety of hardware components. In this section, examples of suchcomponents are described. However, it should be understood that ingeneral, the various steps and techniques discussed herein can beperformed using a variety of different devices and system components,not all of which are expressly set forth.

FIG. 4 is a schematic diagram showing an example sample handlingapparatus 400 in accordance with some example implementations. Samplehandling apparatus 400, also referred to as sample holder 400, includesa first member 404 that holds a first substrate 406 on which a sample302 may be positioned. The first member 404 may include a firstretaining mechanism configured to retain the first substrate 406 in afixed position along an axis and disposed in a first plane. As shown,the sample handling apparatus 400 also includes a second member 410 thatholds a second substrate 412. The second member 410 may include a secondretaining mechanism configured to retain the second substrate 412disposed in a second plane. The second substrate 412 may include abarcoded array (e.g., spatially-barcoded capture probes 306), asdescribed above. As shown, the sample handling apparatus 400 alsoincludes an adjustment mechanism 415 configured to move the secondmember 410. The adjustment mechanism 415 may be coupled to the secondmember 410 and includes a linear actuator 420 configured to move thesecond member 410 along a z axis orthogonal to the second plane. In someaspects, the adjustment mechanism 415 may be alternatively oradditionally coupled to the first member 404.

FIG. 5A depicts an example first member 404 and an example second member410 in accordance with some example implementations. As shown, thesecond member 410 includes a pin 505. As further shown, the first member404 includes an aperture 504. The aperture 504 may be sized andconfigured to mate with the pin 505. In some aspects, the adjustmentmechanism 415 (not shown) may include the pin 505 and the aperture 504.The pin 505 and the aperture 504 mating may result in the first member404 being aligned relative to the second member 410.

FIG. 5B depicts an example of the first member 404 coupled or otherwisemechanically attached to the second member 410 in a sandwichconfiguration (e.g., via the pin 505 and the aperture 504) in accordancewith some example implementations. As shown, the second substrate 412includes a spacer 507 at least partially surrounding the barcoded arrayof the second substrate 412. The spacer 507 may be configured to contactand maintain a minimum spacing between the first substrate 406 and thesecond substrate 412. While the spacer 507 is shown as disposed on thesecond substrate 412, the spacer 507 may additionally or alternativelybe disposed on the first substrate 406.

FIG. 5C depicts an example of the first member 404 coupled to the secondmember 410 in a sandwich configuration including a coupling member 509coupled to the first substrate 406 and the second substrate 412 andconfigured to inhibit movement between the first substrate 406 and thesecond substrate 412 in accordance with some example implementations. Insome aspects, the coupling member 509 includes a magnet that urges thefirst substrate 406 toward the second substrate 412 or vice versa (e.g.,via a magnetic force).

FIG. 6 is a diagram of an example first member 604 and an example secondmember 410 in accordance with some example implementations. As shown inthe left-hand side of FIG. 6 , the first member 604 is coupled to thesecond member 410. The top right-hand side of FIG. 6 depicts the firstmember 604. As shown, the first member 604 is configured to retain twofirst substrates 406. As further shown, the two first substrates 406 aredisposed substantially parallel to each other along a common plane(e.g., an xy-plane) within the first member 604. The first memberincludes a first retaining mechanism 608 configured to retain a firstsubstrate 406. The first retaining mechanism 608 may include springplungers configured to push the first substrate 406 to a position, mayinclude a spring loaded clamp design configured to apply a force to thefirst substrate 406 to maintain contact between the first substrate 406and the first member 604, or the like to retain the first substrate 406in a position in the first member 604. The bottom-right hand side ofFIG. 6 depicts the second member 410. The second member 410 includes asecond retaining mechanism 609 configured to retain the second substrate412. The second retaining mechanism 609 may include spring plungersconfigured to push the second substrate 412 to a position, may include aspring loaded clamp design configured to apply a force to the secondsubstrate 412 to maintain contact between the second substrate 412 andthe second member 410, or the like to retain the second substrate 412 ina position in the second member 410.

FIG. 7 depicts a diagram 700 of a close-up bottom view of the firstmember 404 coupled to the second member 410 and an overlap area 710where the first substrate 406 overlaps with the second substrate 412 inaccordance with some example implementations. The overlap may occuralong an axis orthogonal to the first substrate 406 and/or orthogonal tothe second substrate 412. In some aspects, a camera may capture an imageof the overlap area 710 that may be used as part of the spatial analysisfurther described herein. In some embodiments, the diagram 700 depictsan assembly of the first member 404 coupled to the second member 410having dimensions of 113 mm long and 112 mm wide, although otherdimensions are possible.

FIG. 8 depicts a front cross-sectional view of the sample handlingapparatus 400 in accordance with some example implementations. As shown,the first member 404 and the second member 410 may be configured tomaintain a separation distance 405 between the first substrate 406 andthe second substrate 412. The separation distance 405 may be 19.5 mm inan initial or open position. In some aspects, the adjustment mechanism415 may be configured to adjust the separation distance 405.

FIG. 9 is diagram of an example adjustment mechanism 415 in accordancewith some example implementations. The adjustment mechanism 415 mayinclude a moving plate 916, a bushing 917, a shoulder screw 918, a motorbracket 919, and the linear actuator 420. The moving plate 916 may becoupled to the second member 410 and adjust the separation distance 405along a z axis (e.g., orthogonal to the second substrate 412) by movingthe moving plate 916 up in a superior direction toward the firstsubstrate 406. The movement of the moving plate 906 may be accomplishedby the linear actuator 420 configured to move the second member 410along the axis orthogonal to the second plane at a velocity. Thevelocity may be controlled by a controller communicatively coupled tothe linear actuator 420. For example, the velocity may be configured tomove the moving plate between at least 0.1 mm/sec to 2 mm/sec. In someaspects, the velocity of the moving plate (e.g., closing the sandwich)may affect bubble generation or trapping within the permeabilizationsolution 305. Further, the linear actuator may be configured to move themoving plate 906 with an amount of force (e.g., between 0.1-4.0 poundsof force). The controller may be configured to adjust the velocityand/or the amount of force of the linear actuator 420 to accomplish adesired combination of velocity and force for the moving plate 906.

In some aspects, the velocity of the moving plate (e.g., closing thesandwich) may affect bubble generation or trapping within thepermeabilization solution 305. In some embodiments, the closing speed isselected to minimize bubble generation or trapping within thepermeabilization solution 305. In some embodiments, the closing speed isselected to reduce the time it takes the flow front of a reagent mediumfrom an initial point of contact with the first and second substrate tosweep across the sandwich area (also referred to herein as “closingtime”. In some embodiments, the closing speed is selected to reduce theclosing time to less than about 1100 ms. In some embodiments, theclosing speed is selected to reduce the closing time to less than about1000 ms. In some embodiments, the closing speed is selected to reducethe closing time to less than about 900 ms. In some embodiments, theclosing speed is selected to reduce the closing time to less than about750 ms. In some embodiments, the closing speed is selected to reduce theclosing time to less than about 600 ms. In some embodiments, the closingspeed is selected to reduce the closing time to about 550 ms or less. Insome embodiments, the closing speed is selected to reduce the closingtime to about 370 ms or less. In some embodiments, the closing speed isselected to reduce the closing time to about 200 ms or less. In someembodiments, the closing speed is selected to reduce the closing time toabout 150 ms or less.

FIG. 10 is a perspective view of an example sample handling apparatus400 including an automated second member 410 in accordance with someexample implementations. As shown, the sample handling apparatus 400includes the adjustment mechanism 415. The adjustment mechanism 415 maybe automated such that one or more of the moving plate 916, the bushing917, the shoulder screw 918, the motor bracket 919, and the linearactuator 420 may be controlled by a controller (not shown)communicatively coupled to the adjustment mechanism 415. The controllermay be configured to adjust a position of the second member 410 relativeto the first member 404 (e.g., separation distance 405). The firstmember 404 may be fixed with respect to one or more axes (e.g., the zaxis).

FIG. 11A is a perspective view of the example sample handling apparatus400 including a heater 1108 in accordance with some exampleimplementations. As shown, the sample handling apparatus 400 includesthe heater 1108 as part of the second member 410.

FIG. 11B is a exploded view of an example second member 410 includingthe heater 1108 in accordance with some example implementations. Asshown, the heater 1108 is positioned below or inferior to the secondsubstrate 412 and above (superior to) the second member holder 1110. Theheater 1108 may be configured to heat the second substrate 412 to adesired or target temperature. The second member holder 1110 includes acutout window 1111 for the overlap area 710. The second member holder1110 further includes an epoxy pocket 1112 for the heater 1108 and screwholes 1113 for the first substrate 406 and the second substrate 412parallel alignment. As further shown, the second member 410 includes thesecond retaining mechanism 609. The second retaining mechanism 609 mayinclude a swing clamp, a spring-loaded clamp, or the like to retain thesecond substrate 412 in a position within the second member 410.

FIG. 11C is a graph 1150 of an example desired substrate (e.g., slide)temperature profile over time in accordance with some exampleimplementations. As shown in the graph 1150, the temperature of theslide may hover close to an ambient temperature (e.g., between 18-28°C.) until a trigger time 1160 (e.g., when imaging starts or whensandwiching of the substrates starts). After the trigger time 1160, theheater 1108 may heat the slide and the slide temperature may riselinearly until the slide temperature reaches a threshold temperature tothe desired slide temperature at 1170. After the threshold temperatureis reached, the slide temperature may fluctuate sinusoidally around thedesired slide temperature, T_(set), and may settle within a thresholdamplitude around the desired temperature T_(set). At 1180, the sandwichtimer may complete and the slide temperature may begin to lower andreturn to the ambient temperature. In some aspects, the desiredtemperature may be based on the tissue sample 302, the permeabilizationsolution 305, a starting temperature of the first substrate or thesecond substrate, or the like.

FIG. 12A is a perspective view of an example first member 404 inaccordance with some example implementations. As shown, the first member404 includes a holder plate 1210 and the first retaining mechanism 608retaining the first substrate 406 within the first member 404.

FIG. 12B is an exploded view of the example first member 404 of FIG. 12Ain accordance with some example implementations. As shown, the firstmember 404 includes the holder plate 1210, an insulation gasket 1211, athermal pad 1212, and a thermoelectric cooler (TEC) 1213. The holderplate 1210 may be configured to receive and retain the first substrate406. The insulation gasket 1211, the thermal pad 1212, and/or the TEC1213 may be configured to adjust and/or maintain a desired or targettemperature for the first substrate 406.

FIG. 13A is a perspective cross-section view of an example first member404 in accordance with some example implementations. As shown, the firstmember 404 of FIG. 13A includes the holder plate 1210, the insulationgasket 1211, the TEC 1213, and a heat sink block 1214.

FIG. 13B is a perspective view of the example holder plate 1210 of FIG.13A in accordance with some example implementations. As shown, theholder plate 1210 includes a cutout window 1216 for the overlap area710.

FIG. 13C is a perspective view of the example heat sink block 1214 ofFIG. 13A in accordance with some example implementations. As shown, theheat sink block 1214 includes a cut out window 1217 for the overlap area710.

FIG. 14A is a perspective view of an example sample handling apparatus1400 in a closed position in accordance with some exampleimplementations. As shown, the sample handling apparatus 1400 includes afirst member 1404, a second member 1410, an image capture device 1420, afirst substrate 1406, a hinge 1415, and a mirror 1416. The hinge 1415may be configured to allow the first member 1404 to be positioned in anopen or closed configuration by opening and/or closing the first member1404 in a clamshell manner along the hinge 1415.

FIG. 14B is a perspective view of the example sample handling apparatus1400 in an open position in accordance with some exampleimplementations. As shown, the sample handling apparatus 1400 includesone or more first retaining mechanisms 1408 configured to retain one ormore first substrates 1406. In the example of FIG. 14B, the first member1404 is configured to retain two first substrates 1406, however thefirst member 1404 may be configured to retain more or fewer firstsubstrates 1406.

In some aspects, when the sample handling apparatus 1400 is in an openposition (as in FIG. 14B), the first substrate 1406 and/or the secondsubstrate 1412 may be loaded and positioned within the sample handlingapparatus 1400 such as within the first member 1404 and the secondmember 1410, respectively. As noted, the hinge 1415 may allow the firstmember 1404 to close over the second member 1410 and form a sandwichconfiguration (e.g., the sandwich configuration shown in FIG. 3 ).

In some aspects, after the first member 1404 closes over the secondmember 1410, an adjustment mechanism (not shown) of the sample handlingapparatus 1400 may actuate the first member 1404 and/or the secondmember 1410 to form the sandwich configuration for the permeabilizationstep (e.g., bringing the first substrate 1406 and the second substrate1412 closer to each other and within a threshold distance for thesandwich configuration). The adjustment mechanism may be configured tocontrol a speed, an angle, or the like of the sandwich configuration.

In some embodiments, the tissue sample (e.g., sample 302) may be alignedwithin the first member 1404 (e.g., via the first retaining mechanism1408) prior to closing the first member 1404 such that a desired regionof interest of the sample 302 is aligned with the barcoded array of thegene expression slide (e.g., the slide 304), e.g., when the first andsecond substrates are aligned in the sandwich configuration. Suchalignment may be accomplished manually (e.g., by a user) orautomatically (e.g., via an automated alignment mechanism). After orbefore alignment, spacers may be applied to the first substrate 1406and/or the second substrate 1412 to maintain a minimum spacing betweenthe first substrate 1406 and the second substrate 1412 duringsandwiching. In some aspects, the permeabilization solution (e.g.,permeabilization solution 305) may be applied to the first substrate1406 and/or the second substrate 1412. The first member 1404 may thenclose over the second member 1410 and form the sandwich configuration.Analytes and/or mRNA transcripts 308 may be captured by the captureprobes 306 and may be processed for spatial analysis.

In some embodiments, during the permeabilization step, the image capturedevice 1420 may capture images of the overlap area (e.g., overlap area710) between the tissue 302 and the capture probes 306. If more than onefirst substrates 1406 and/or second substrates 1412 are present withinthe sample handling apparatus 1400, the image capture device 1420 may beconfigured to capture one or more images of one or more overlap areas710.

The image capture device 1420 and the sample handling apparatus 1400 canbe configured to capture images in one or more image capture modes. Theimage capture modes can include programmatic settings and parametersthat can be applied by a user and can configure the image capture device1420 and the sample handling apparatus 1400 to capture images in avariety of workflows or experimental conditions. The image capture modescan allow image capture and image data generation for a variety of usecases, including different sample stain conditions, differentfluorescence conditions, and different illumination requirements. Inthis way, the sample handling apparatus 1400 can support a variety ofimaging needs at varying resolutions that may be independent of aparticular assay or experimental workflow.

In some embodiments, the image capture modes can include a free capturemode and an assay capture mode. The free capture mode may not beassociates with capturing image data in regard to a particular assay orassay workflow. Instead, the free capture mode can enable users toacquire image data as they wish, in an ad hoc manner, or within acustomized or alternate experimental workflow. For example, H&E stainedtissue samples can be imaged prior to removing the hematoxylin and afterremoving the hematoxylin.

The assay capture mode can be associated with and performed within aparticular assay or assay workflow. The assay or assay workflow caninclude capturing images of samples that have been stained. For example,H&E stained tissue samples that can be H&E stained with hematoxylin andeosin can be imaged in an assay or assay workflow to generate RGB imagedata. When configured in assay capture mode, the sample handlingapparatus 1400 can capture image data before, during, or afterpermeabilization steps that can be performed during an assay asdescribed herein.

The captured image data acquired in any one or the image capture modescan be used in the image registration methods performed by the samplehandling apparatus 1400. In some embodiments, the image data acquired inassay capture more and/or the free capture mode can be acquired in anprogrammatically automated manner or in a manual manner defined by userinputs provided to the sample handling apparatus 1400.

In some embodiments, the image data captured in the image capture modesdescribed herein can include image capture mode data. The image capturemode data can be a data such as a tag, a parameter, or an identifieridentifying the particular image capture mode that the sample handlingapparatus 1400 was operating in when the image data was captured usingthe image capture device 1420. In some embodiments, any of the samplehandling apparatuses 400, 1400, and 3000 described herein can includesoftware implementing any one of the image captured modes. When executedby a data processor, the software can cause the image capture deviceconfigured in any of sample handling apparatuses 400, 1400, and 3000 toacquire image data as described herein.

FIG. 15 is a perspective view of the example sample handling apparatus1400 in accordance with some example implementations. As shown, thesample handling apparatus 1400 is in an open position with the firstmember 1404 disposed above (superior to) the second member 1410. Asnoted above, the first member 1404 and/or the second member 1410 may beconfigured to hold one or more substrates (e.g., first substrates 1406and/or second substrates 1412, respectively). The sample handlingapparatus 1400 further includes a user interface 1525. The userinterface 1525 may include a touchscreen display for displayinginformation relating to the sample handling apparatus and receiving userinput controls for controlling aspects or functions of the samplehandling apparatus 1400.

FIG. 16A is a perspective view of the example sample handling apparatus1400 in accordance with some example implementations.

FIG. 16B is a front view of the example sample handling apparatus 1400showing example dimensions of the apparatus 1400 in accordance with someexample implementations. As shown, the sample handling apparatus mayhave a width of 300 mm and a height of 255 mm, although other dimensionsare possible. The second member 1410 may have a height of 150 mm and awidth of 300 mm, although other dimensions are possible.

FIG. 16C is a side view of the example sample handling apparatus 1400showing example dimensions of the apparatus 1400 in accordance with someexample implementations. As shown, the sample handling apparatus mayhave a depth of 405 mm, although other dimensions are possible.

III. Sample and Array Alignment Devices and Methods

Spatial analysis workflows described herein generally involve contactinga sample with an array of features. With such workflows, aligning thesample with the array is an important step in performing spatialomic(e.g., spatial transcriptomic) assays. The ability to efficientlygenerate robust experimental data for a given sample can depend greatlyon the alignment of the sample and the array. Traditional techniquesrequire samples to be placed directly onto the array. This approach canrequire skilled personnel and additional experimental time to prepare asection of the sample and to mount the section of the sample directly onthe array. Misalignment of the sample and the array can result in wastedresources, extended sample preparation time, and inefficient use ofsamples, which may be limited in quantity.

The systems, methods, and computer readable mediums described herein canenable efficient and precise alignment of samples and arrays, thusfacilitating the spatialomic (e.g., spatial transcriptomic) imaging andanalysis workflows or assays described herein. Samples, such as portionsof tissue, can be placed on a first substrate. The first substrate caninclude a slide onto which a user can place a sample of the tissue. Anarray, such as a reagent array, can be formed on a second substrate. Thesecond substrate can include a slide and the array can be formed on thesecond substrate. The use of separate substrates for the sample and thearray can beneficially allow user to perform the spatialomic (e.g.,spatial transcriptomic) assays described herein without requiring thesample to be placed onto an array substrate. The sample holder andmethods of use described herein can improve the ease by which usersprovide samples for spatial transcriptomic analysis. For example, thesystems and methods described herein alleviate users from possessingadvanced sample or tissue sectioning or mounting expertise. Additionalbenefits of utilizing separate substrates for samples and arrays caninclude improved sample preparation and sample imaging times, greaterability to perform region of interest (ROI) selection, and moreefficient use of samples and array substrates. The systems, methods, andcomputer readable mediums described herein can further enable users toselect the best sections of a sample to commit to sequencing workflows.Some tissue samples or portions of the tissue samples can be damagedduring mounting. For examples, the tissue samples or portions of thetissue samples can be folded over on themselves. The systems, methods,and computer readable mediums described herein can further enable usersto confirm relevant pathology and/or biology prior to committing tosequencing workflows.

The sample substrate and the array substrate, and thus, the sample andthe array, can be aligned using the instrument and processes describedherein. The alignment techniques and methods described herein cangenerate more accurate spatialomic (e.g., spatial transcriptomic) assayresults due to the improved alignment of samples with an array, such asa reagent array.

In some embodiments, a workflow described herein comprises contacting asample disposed on an area of a first substrate with at least onefeature array of a second substrate. In some embodiments, the contactingcomprises bringing the two substrates into proximity such that thesample on the first substrate may be aligned with the barcoded array onthe second substrate. In some instances, the contacting is achieved byarranging the first substrate and the second substrate in a sandwichassembly. In some embodiments, the workflow comprises a prior step ofmounting the sample onto the first substrate.

Alignment of the sample on the first substrate with the array on thesecond substrate may be achieved manually or automatically (e.g., via amotorized alignment). In some aspects, manual alignment may be done withminimal optical or mechanical assistance and may result in limitedprecision when aligning a desired region of interest for the sample andthe barcoded array. Additionally, adjustments to alignment done manuallymay be time-consuming due to the relatively small time requirementsduring the permeabilization step.

It may be desirable to perform real-time alignment of a tissue slide(e.g., the pathology slide 303) with an array slide (e.g., the slide 304with barcoded capture probes 306). In some implementations, suchreal-time alignment may be achieved via motorized stages and actuatorsof a sample handling apparatus (e.g., the sample handling apparatus 400,the sample handling apparatus 1400, or the like).

FIGS. 17A-17C depict a workflow 1700 for loading slides into a samplehandling apparatus for later alignment in accordance with some exampleimplementations.

FIG. 17A depicts the example sample handling apparatus 400 with noslides loaded into the apparatus 400. As shown, the sample handlingapparatus 400 includes two first members 404, the second member 410, andan image capture device 1720. The image capture device 1720 cancorrespond to the image capture device 1420 shown and described inrelation to FIGS. 14A-14B. While two first members 404 and a singlesecond member 410 are shown in the FIGS. 17A-17C, it will be appreciatedthat more or fewer first members 404 and/or second members 410 arepossible. While the image capture device 1720 is shown in a positioninferior to the second member 410, other locations for the image capturedevice 1720 are possible and more or fewer image capture devices 1720are also possible.

FIG. 17B depicts the sample handling apparatus 400 with a geneexpression slide (e.g., slide 304 with barcoded capture probes 306)loaded into the second member 410. A bottom portion of the FIG. 17Bshows a top view of the slide 304. As shown, the slide 304 includes twoarray regions with barcoded capture probes 306A and 306B, respectively.

FIG. 17C depicts the sample handling apparatus 400 with a histologyslide 303A and a pathology slide 303B loaded into first members 404A and404B, respectively. As shown, the histology slide 303A and the pathologyslide 303B include tissue samples 302A and 302B, respectively. A bottomportion of FIG. 17C shows a top view of an initial alignment of the geneexpression slide 304 with the histology slide 303A and the pathologyslide 303B after loading.

FIGS. 18A-18C depict a workflow 1800 for aligning the loaded slides ofthe sample handling apparatus 400. FIGS. 18A-18C are similar to andadapted from FIGS. 17A-17C and the workflow 1800 may occur after theworkflow 1700.

FIG. 18A shows the sample handling apparatus 400 of FIG. 17C with thesecond member 410 moved up towards the first members 404A and 404B. Insome aspects, bringing the second member 410 closer to the first members404 may make alignment of the desired regions of the slides 303 and 304easier to achieve. The movement of the second member 410 may beperformed by an adjustment mechanism (e.g., adjustment mechanism 415) ofthe sample handling apparatus 400. The bottom portion of FIG. 18A showsa top view of the initial alignment of the slides 303A, 303B, and 304.As further shown, the tissue samples 302A and 302B include regions ofinterest 1802A and 1802B, respectively. The regions of interest 1802Aand 1802B may be selected by a user prior to loading the slides 303 intothe sample handling apparatus 400 or may be determined after imaging ofthe tissue samples 302A and 302B. In some embodiments, the regions ofinterests 1802 can be annotations that can be manually applied on thehistology slide 303A, the pathology slide 303B, or the array slide 304by a user. For example, the user can annotate the region of interest1802 on the slides using a marker, a stamp, or a sticker. In someembodiments, the regions of interest 1802 can be manually applied on animage of the tissue samples 302A and/or 302B, or on an image of thetissue samples 302A or 302B that have been overlaid with the array slide304 by a user.

In some embodiments, the regions of interest 1802 can be automaticallyapplied on the histology slide 303A and/or the pathology slide 303B, oron the array slide 304 based on inputs provided to the sample handlingapparatus 400 by a user. In some embodiments, the regions of interest1802 can be selected and annotated on a display of a computing devicecoupled to the sample handling apparatus 400. In some embodiments, thesample handling apparatus 400 can align the histology slide 303A and/orthe pathology slide 303B with the array slide 304 based on the selectedregions of interest 1802. In some embodiments, the sample handlingapparatus 400 can read or determine the annotations marking the regionsof interest 1802 via image capture, such as using the image capturedevice 1720, and using image processing techniques. In some embodiments,the annotating the regions of interest 1802 can be performed by adedicated machine, separate from the sample handling apparatus 400, suchthat the dedicated machine applies the annotation markings to thehistology slide 303A, the pathology slide 303B, or the array slide 304after the user has selected the regions of interest 1802 via aninterface provided with the sample handling apparatus 400. FIG. 18Bdepicts an alignment of the barcoded capture probe area 306A with thetissue sample region of interest 1802A. The alignment may occur in an xyplane and by moving the first member 404A in an xy direction tooptically and vertically align the capture probes 306A with the regionof interest 1802A. For example, as shown in the bottom portion of FIG.18B, the top view of the slides 303A and 304 show that the captureprobes 306A are aligned with the region of interest 1802A of the tissuesample 302A (e.g., dashed lines). In some aspects, the image capturedevice 1720 may aid in the alignment of the slides 303 and 304 byproviding images of the capture probes 306A, the sample 302A, and/or theregion of interest 1802A. In some aspects, the alignment precision maybe within approximately 0.1-0.5 mm. In some embodiments, the automatedalignment described herein can enable alignment precision within 1-10microns.

In some aspects, the movement of the first member 404A may be performedby an alignment mechanism configured to move the slide 303A (e.g., thefirst substrate 406, the first substrate 1406, or the like) along afirst plane (e.g., the xy plane of the histology slide 303A). In someimplementations, the alignment mechanism may be configured to move thegene expression slide 304 (e.g., the second substrate 412, the secondsubstrate 1412, or the like) along a second plane (e.g., the xy plane ofthe slide 304).

FIG. 18C depicts an alignment of the barcoded capture probe area 306Bwith the tissue sample region of interest 1802B. The alignment may occurin an xy plane and by moving the first member 404B in an xy direction tooptically and vertically align the capture probes 306B with the regionof interest 1802B. For example, as shown in the bottom portion of FIG.18C, the top view of the slides 303B and 304 show that the captureprobes 306B are aligned with the region of interest 1802B of the tissuesample 302B. In some aspects, the image capture device 1720 may aid inthe alignment of the slides 303 and 304 by providing images of thecapture probes 306B, the sample 302B, and/or the region of interest1802B.

In some aspects, the movement of the first member 404B may be performedby an alignment mechanism configured to move the slide 303B (e.g., thefirst substrate 406, the first substrate 1406, or the like) along afirst plane (e.g., the xy plane of the slide 303B). In someimplementations, the alignment mechanism may be configured to move thegene expression slide 304 (e.g., the second substrate 412, the secondsubstrate 1412, or the like) along a second plane (e.g., the xy plane ofthe slide 304).

FIG. 19 is a process flow diagram illustrating an example process 1900for aligning a sample area with an array area according to someimplementations of the current subject matter. At 1910, a firstsubstrate can be received within a first retaining mechanism of a samplehandling apparatus, such as sample handling apparatuses 400, 1400, or3000. A user can provide or position the first substrate within thefirst retaining mechanism of the sample handling apparatus 400. Thefirst substrate can include a sample applied to the first substrate by auser. The first substrate can also include a sample area into which thesample is to be placed. The first substrate can further include a samplearea indicator identifying the sample area. In some embodiments, thefirst substrate can include a fiducial mark. The first retainingmechanism can include one or more spring members configured to apply aforce to the first substrate to maintain contact between the firstsubstrate and a first member of the sample handling apparatus 400 onwhich the first retaining mechanism is configured.

At 1920, a second substrate can be received within a second retainingmechanism of the sample handling apparatus 400. The second substrate caninclude an array of reagent medium formed within an array area indicatoridentifying the array on the second substrate. In some embodiments, thearray area indicator can be provided on the sample handling apparatus400. A user can provide or position the second substrate within thesecond retaining mechanism of the sample handling apparatus 400. Thesecond retaining mechanism can include one or more spring membersconfigured to apply a force to the second substrate to maintain contactbetween the second substrate and a second member of the sample holder onwhich the second retaining mechanism is configured.

At 1930, a location of the first substrate can be adjusted relative tothe second substrate to cause all or a portion of the sample area of thefirst substrate to be aligned with the array area of the secondsubstrate. In some embodiments, adjusting the location of the firstsubstrate relative to the second substrate can be performed to cause thesample area indicator to be aligned with the array area indicator. Insome embodiments, the location of the first substrate relative to thesecond substrate can be adjusted by a user. For example, the user canmanually manipulate the first member and/or the second member of thesample holder so as to adjust a location of the first substrate and/orthe second substrate within the sample holder to cause the sample areato be aligned with the array area. In some embodiments, the location ofthe first substrate can be adjusted relative to the second substrate,which can be fixed in position within the sample handling apparatus 400.In some embodiments, the location of the second substrate can beadjusted relative to the first substrate, which can be fixed in positionwithin the sample handling apparatus 400. In some embodiments, thesecond substrate can be fixed in place within the sample handlingapparatus 400 and the first retaining mechanism can be adjusted to causeall or a portion of the sample area to be aligned with the array area.

In some embodiments, a user can adjust the location of the firstsubstrate and/or the second substrate while viewing the first substrateand/or the second substrate within the sample handling apparatus 400.For example, the user can view the first substrate and the secondsubstrate via a microscope of the instrument configured to provide thesample holder within a field of view of the microscope. In someembodiments, the instrument can include a display providing a view ofthe first substrate and the second substrate within the sample handlingapparatus.

In some embodiments, adjusting the location of the first substraterelative to the second substrate can further include viewing the firstsubstrate and the second substrate within the sample holder andadjusting the first retaining mechanism and/or the second retainingmechanism to cause all or a portion of the sample area to be alignedwith the array area. In this way, the sample handling apparatus 400 canadvantageously support efficient and precise alignment by providingmultiple, different ways to perform the alignment. In some embodiments,the adjusting can be performed in the absence of a sample area indicatorconfigured on the first substrate and/or in the absence of an array areaindicator configured on the second substrate.

In some embodiments, the location of the first substrate and/or thesecond substrate can be adjusted within the sample holder by a userinteracting with a physical positioning device configured on the samplehandling apparatus 400, or on the instrument while viewing the firstsubstrate and the second substrate. The physical positioning device caninclude a joy stick, a pointing stick, a button, or the like. In someembodiments, the instrument can be configured with computer-readable,executable instructions stored in a memory of the instrument. Theinstructions, when executed, can perform the adjusting automaticallybased on image data associated with the sample handling apparatus 400,the first substrate, and/or the second substrate. In some embodiments,the instrument can be configured with a display providing a graphicaluser interface (GUI). A user can interact with the GUI to adjust thelocation of the first substrate relative to the second substrate tocause all or a portion of the sample area indicator to be aligned withrespect to the array area indicator.

FIG. 20 depicts a workflow 2000 for adjusting a location of the firstsubstrate relative to the second substrate to align all or a portion ofa sample area with an array area. As shown in FIG. 20 , and withreference to operation 1930 described in relation to FIG. 19 , a firstsubstrate 2005 can include a sample 2010 positioned by a user within asample area 2015 identified by a sample area indicator 2020 of the firstsubstrate 2005. In some embodiments, the first substrate 2005 may notinclude the sample area indicator 2020. The second substrate 2025 caninclude one or more array area indicators 2030 indicating a location ofan array area 2035. Each array area 2035 can include an array 2040therein.

The sample handling apparatus 400 can be configured to enable adjustmentof the first substrate 2005 and/or the second substrate 2025 along afirst axis 2045 and a second axis 2050. The first axis 2045 can beconsidered a later axis within a transverse plane corresponding to themounting surface in which the first substrate 2005 and the secondsubstrate 2025 are received within the sample handling apparatus 400.The second axis 2050 can be considered a longitudinal axis within thetransverse plane corresponding to the mounting surface in which thefirst substrate 2005 and the second substrate 2025 are received withinthe sample handling apparatus 400.

As shown in FIG. 20 , adjusting 2055 the first substrate 2005 relativeto the second substrate 2025 can be performed to cause all or a portionof the sample area 2015 to be aligned with the array area 2035.Additionally, or alternatively, the adjusting 2055 (e.g., operation 1930of FIG. 19 ) can further cause the sample area indicator 2020 to bealigned with respect to the array area indicator 2030. In this way, theadjusting 2055 can cause the sample 2010 to be aligned with the array2040.

FIGS. 21A-21B depict a workflow 2100 for adjusting a location of thefirst substrate relative to the second substrate based on an array areaindicator configured within a sample handling apparatus 400 according tosome implementations of the current subject matter. As shown in FIG.21A, a sample handling apparatus 400 can include a retaining mechanism2105 configured with a surface 2110. The surface 2110 can include anarray area indicator 2115 identifying an array area 2120. In someembodiments, part or all of the surface 2110 is transparent. In someembodiments, the array area indicator 2115 identifies the position of anarray on the second substrate when the first and second substrates arebrought into a sandwich configuration (e.g., the sandwich configurationdepicted in FIG. 3 ). The array area indicator 2115 can be configured ona first surface of the retaining mechanism 2105, for example a firstsurface corresponding to the surface 2110. In some embodiments, thearray area indicator 2115 can be configured on a second surface of theretaining mechanism 2105, the second surface opposite the surface 2110.In some embodiments, a portion of the retaining mechanism 2105 caninclude the surface 2110. In some embodiments, the array area indicator2115 is transparent and can be backlit. In some embodiments, the surface2110 can be frontlit instead of backlit. In some embodiments, thesurface 2110 may not include lighting and can be lit via ambientlighting.

As shown in FIG. 21B, a first substrate 2125 including a sample 2130positioned within a sample area 2135 can be received within theretaining mechanism 2105. Adjusting 2140 the substrate 2125 relative tothe transparent surface 2110 can be performed to cause all or a portionof the sample area 2135 to be aligned with the array area 2120. Thefirst and second substrates may be then brought into sandwichconfiguration (e.g., the sandwich configuration depicted in FIG. 3 )such that the sample area 2135 is aligned with an array on the secondsubstrate.

FIGS. 21C-21D depict a workflow for adjusting a location of multiplefirst substrates relative to the second substrate based on multiplearray area indicators configured within a sample holder according tosome implementations of the current subject matter. As shown in FIG.21C, a sample handling apparatus 400 can include a retaining mechanism2145 configured with a surface 2150. The surface 2150 can include afirst array area indicator 2155 identifying a first array area 2160 anda second array area indicator 2165 identifying a second array area 2170.In some embodiments, part of all of the surface 2150 is transparent. Insome embodiments, the array area indicators 2155 and 2165 identify theposition of the arrays on the second substrate when the first and secondsubstrates are brought into a sandwich configuration (e.g., the sandwichconfiguration depicted in FIG. 3 ). The array area indicators 2155 and2165 can be configured on a first surface of the retaining mechanism2145, for example a first surface corresponding to the surface 2150. Insome embodiments, the array area indicators 2155 and 2165 can beconfigured on a second surface of the retaining mechanism 2145, thesecond surface opposite the surface 2150. As shown in FIG. 21C, a firstsubstrate 2125 including a first sample 2130 positioned within a samplearea 2135 can be received within the retaining mechanism 2145. A secondsubstrate 2175 including second sample 2180 positioned within a secondsample area 2185 can also be received within the retaining mechanism2145.

As shown in FIG. 21C and FIG. 21D, adjusting 2190 the first substrate2125 relative to the surface 2150 can be performed to cause all or aportion of the first sample area 2135 to be aligned with the first arrayarea 2160. The second substrate 2175 can be also adjusted 2190 relativeto the surface 2150 to cause all or a portion of the second sample area2185 to be aligned with the second array area 2170. The first substrate2125 and the second substrate 2175 may be then brought into sandwichconfiguration (e.g., the sandwich configuration depicted in FIG. 3 )such that the first sample area 2135 is aligned with an array configuredwithin the first array area 2160 and the second sample area 2185 isaligned with the an array configured within the second array area 2170.

FIGS. 22A-22C depict a workflow 2200 for indicating a sample area of asubstrate according to some implementations of the current subjectmatter. The substrate described in relation to FIGS. 22A-22C can beequivalent to the first substrate described in relation to FIGS. 19 and20 . To indicate a sample area of a substrate on to which a sample isplaced a variety of embodiments can be considered.

As shown in FIG. 22A, a substrate 2205 can include a sample areaindicator 2210. The sample area indicator 2210 can be provided by themanufacturer of the substrate such that the sample area indicator isprovided on the substrate 2205 prior to a user placing a sample 2220onto the substrate 2205. In some embodiments, the sample area indicator2210 can be applied to a first side of the substrate 2205 prior toapplying the sample 2220 to the first side of the substrate 2205. Insome embodiments, the sample area indicator 2210 can be applied to asecond side of the substrate 2205. The second side of the substrate 2205can be opposite the first side of the substrate 2205. In someembodiments, the sample area indicator 2210 can be applied to the secondside of the substrate 2205 after the sample 2220 has been applied to thefirst side of the substrate 2205.

As further shown in FIG. 22A, the substrate 2205 can include a fiducialmark 2215. The fiducial mark 2215 can be applied to the first side ofthe substrate 2205 or to the second side of the substrate 2205. Thefiducial mark 2215 can be used to aid alignment of the sample area on afirst substrate 2205 with an array area on second substrate, such assecond substrate 2025 described in relation to FIG. 20 . The fiducialmark 2215 can include a variety of non-limiting shapes and formats, suchas variously shaped applied or embedded markings or etchings, suitableto provide a fiducial reference on the substrate 2205.

As shown in FIG. 22B, the sample area indicator can include a stamp or asticker 2225. The stamp or sticker 2225 can be applied to the secondside of the substrate 2205 after the sample 2220 has been applied to thefirst side of the substrate 2205 by a user.

As shown in FIG. 22C, the sample area indicator can be applied as adrawing 2230 on the second side of the substrate 2205 after the sample2220 has been applied to the first side of the substrate 2205 by a user.In some embodiments, the drawing 2230 can be drawn by a user with amarker suitable for marking the substrate 2205.

In some embodiments, informational labels with printed guides can beprovided to assist users in tissue placement onto slides. Fiducialmarkers (e.g., dots, numbers and letters) can provide a visual guide forthe printed array location on the slide. Dots can indicate the center ofan array while numbers and letters can identify individual wells. Insome embodiments, informational labels with printed guides reducesurface smudging, and reduce direct contact with the cryostat surfacesby acting as a physical barrier between the slide and other surfaces. Insome embodiments, informational labels are disposable.

In some embodiments, informational labels may be transparent.Informational labels may have printed guides that are printed with ink(e.g., white ink, black ink, color ink, or fluorescent ink). In someembodiments, informational labels may be printed using thermal printingwhich uses heat to transfer impressions to the informational label. Insome embodiments, etching can be used to print guides on theinformational label. Informational label texture can be altered byprinting different patterns on the surface of the informational label.In some embodiments, an informational label has a matte finish. In someembodiments, an informational label has a glossy finish. Informationallabels can have holes or cut-outs in the interior of the informationallabel. In some embodiments, an informational label occupies all of theretaining mechanism and/or transparent surface upon which samplesubstrates can be received within the sample handling apparatus 400,1400, and 3000. In some embodiments, an informational label occupies aportion of the retaining mechanism and/or transparent surface of thesample handling apparatus 400, 1400, and 3000. In some embodiments, aninformational label is capable of thermal and electrical conductivity.In some embodiments, an informational label is capable of thermalconductivity. In some embodiments, an informational label is capable ofelectrical conductivity. In some embodiments, an informational labelcontains metadata. Non-limiting examples of metadata include tissueplacement guides, array/well identification, slide identificationbarcode, slide orientation, expiration date, type of slide, dimension ofslide, or other instructions for the user. In some embodiments, afixture could be used to hold the slide in place to apply theinformational label and prevent damage to the slide. Using such fixtureto apply the informational label can reduce surface smudging whileapplying the informational label to the slide.

FIG. 23 is a process flow diagram illustrating an example process 2300for automatically determining a sample area indicator based on areceived image of the sample according to some implementations of thecurrent subject matter. The system, methods, and mediums describedherein can be configured to determine a sample area indicator based onan image of a sample. At 2310, an image of a sample can be received by adata processor of a computing device communicatively coupled to a samplehandling apparatus 400. The sample handling apparatus 400 can receiveand retain a substrate including the sample therein. The computingdevice can be further communicatively coupled to an image capture device1720, such as a microscope, a camera, an optical sensor, an imagingdevice, or the like configured to acquire and provide an image of thesample to the computing device. In some embodiments, the data processorof the computing device can be configured to receive the image of thesample from a data processor of a remote computing devicecommunicatively coupled to the computing device at which the process2300 is performed.

At 2320, the data processor can provide the image of the sample fordisplay via a display of the computing device. In some embodiments, theimage of the sample can be provided for display via a GUI configuredwithin the display of the computing device.

At 2330, the data processor can receive an input identifying the samplearea indicator based on the provided image. For example, the display ofthe computing device can include a touch-screen display configured toreceive a user input identifying the sample area indicator on thedisplayed image. In some embodiments, the GUI can be configured toreceive a user provided input identifying the sample area indicator.

At 2340, the data processor can automatically determine the sample areaindicator based on the image. The data processor can be configured toaccess and execute computer-readable, executable instructions configuredto automatically determine the sample area indicator based on a varietyof features included in the image. For example, the data processor canautomatically determine the sample area indicator based on an outline ofthe tissue present within the image. This approach can be used when thesample area is smaller than the array area. In some embodiments, thedata processor can automatically determine the sample area indicatorbased on a stamp or a sticker that is visible in the image and wasapplied to the first substrate by a user. In some embodiments, the dataprocessor can automatically determine the sample area indicator based ona fiducial mark located on the first substrate that is visible in theimage. In some embodiments, the data processor can automaticallydetermine the sample area indicator based on a drawing that is visiblein the image and was applied to the first substrate by a user.

In some embodiments, the data processor can access and executecomputer-readable, executable instructions configured to automaticallydetermine the sample area indicator based on sample area indicator datawhich can be stored in a memory of the computing device. In someembodiments, the sample area indicator data can be imported into thecomputing device from a second computing device that is remote from andcommunicatively coupled to the computing device automaticallydetermining the sample area indicator associated with the sample in theimage.

In some embodiments, the data processor can access and executecomputer-readable, executable instructions configured to automaticallydetermine the sample area indicator based on processing the sample imageusing image segmentation functionality. In some embodiments, the dataprocessor can access and execute computer-readable, executableinstructions configured to automatically determine the sample areaindicator based on a type of sample, a size of sample, a shape of thesample, and/or an area of the sample.

FIGS. 24A-24B depict a workflow 2400 for receiving an input identifyinga sample area indicator based on an image of a sample as described inrelation to operation 2330 of FIG. 23 . As shown in FIG. 24A, acomputing device 2405 can include a display 2410. The display 2410 canbe configured to provide an image 2415 of a sample. As shown in FIG.24B, a user may interact with the display 2410 to provide an inputidentifying the sample area indicator 2420. For example, the user canmanipulate a mouse or other input device in relation to the image 2415of the sample so as to provide an input identifying the sample areaindicator 2420. The user input can be provided to select all or aportion of the image 2415 to be associated with the sample areaindicator 2420. The selection can be provided by the user dragging acursor 2425 over the image 2415 to form the sample area indicator 2420.In some embodiments, the input can be provided by a user cropping theimage 2415 such that the perimeter of the cropped image forms the samplearea indicator 2420.

FIG. 25 is a process flow diagram illustrating an example process 2500for automatically determining a sample area indicator based on aplurality of received video images according to some implementations ofthe current subject matter. At 2510, a data processor of a computingdevice communicatively coupled to a sample handling apparatus 400 canreceive a plurality of video images. The plurality of video images canbe acquired by and received from via an image capture device 1720, suchas a microscope, a camera, an optical sensor, an imaging device, or thelike, communicatively coupled to the data processor. The plurality ofvideo images can include the sample positioned on a first substrate andthe array located on the second substrate. The plurality of video imagescan include the second substrate overlaid atop the first substrate. Insome embodiments, the data processor of the computing device can beconfigured to receive the image of the sample from a data processor of aremote computing device communicatively coupled to the computing deviceat which the process 2500 is performed.

At 2520, the data processor can provide the plurality of video imagesfor display via a display of the computing device. In some embodiments,the plurality of video images can be provided for display via a GUIconfigured within the display of the computing device. In someembodiments, the plurality of video images can be provided to a dataprocessor of a second computing device. The second computing device canbe remote from the first computing device and can be communicativelycoupled to the first computing device at which the plurality of videoimages were first received. The second computing device can beconfigured to provide the plurality of video images for display via adisplay of the second computing device. In some embodiments, the secondcomputing device can be configured to receive an input from a useridentifying a sample area indicator associated with the samplepositioned on the first substrate. The user can provide the inputidentifying the sample area indicator to the second computing device aspreviously described above.

At 2530, a user can manually adjust a first retaining mechanism of thesample handling apparatus 400 to cause the sample area of the firstsubstrate to be aligned with the array area of the second substrate. Insome embodiments, the user can adjust the first retaining mechanism ofthe sample handling apparatus 400 to cause the sample area of the firstsubstrate to be aligned with an array area configured within the samplehandling apparatus 400. The user can adjust the first retainingmechanism based on viewing the plurality of video images provided by thefirst computing device or the second computing device.

At 2540, in addition, or in alternative, to the manual adjustmentperformed at 2530, the data processor of the first computing device canautomatically determine the sample area indicator based on the pluralityof video images. The data processor of the first computing device can beconfigured to access and execute computer-readable, executableinstructions configured to automatically determine the sample areaindicator based on a variety of features included in the plurality ofvideo images. For example, the data processor can automaticallydetermine the sample area indicator based on an outline of the tissuepresent within the plurality of video images. This approach can be usedwhen the sample area is smaller than the array area. In someembodiments, the data processor can automatically determine the samplearea indicator based on a stamp or a sticker that is visible in theplurality of video images and was applied to the first substrate by auser. In some embodiments, the data processor can automaticallydetermine the sample area indicator based on a fiducial mark located onthe first substrate that is visible in the plurality of video images. Insome embodiments, the data processor can automatically determine thesample area indicator based on a drawing that is visible in theplurality of video images and was applied to the first substrate by auser.

In some embodiments, the data processor can access and executecomputer-readable, executable instructions configured to automaticallydetermine the sample area indicator based on sample area indicator datawhich can be stored in a memory of the computing device. In someembodiments, the sample area indicator data can be imported into thecomputing device from a second computing device that is remote from andcommunicatively coupled to the computing device automaticallydetermining the sample area indicator associated with the sample in theplurality of video images.

At 2550, the data processor of the first computing device can performthe adjusting automatically based on the automatically determined samplearea indicator. The computing device can be configured to automaticallyadjust the location of the first substrate relative to the secondsubstrate to cause all or a portion of the sample area to be alignedwith an array area of the second substrate via a controller that can becommunicatively coupled to the sample handling apparatus 400 and to thefirst computing device. The controller can receive input signals fromthe data processor and can generate control signals causing the firstretaining mechanism or the second retaining mechanism to translatewithin the sample handling apparatus 400 and there by adjust thelocation of the first substrate or the second substrate, respectively.

In some embodiments, the data processor of a second computing device,communicatively coupled to the data processor of the first computingdevice, can similarly be coupled to the controller and to the samplehandling apparatus 400. The data processor of the second computingdevice can generate input signals to the controller and can cause thecontroller to generate control signals causing first retaining mechanismor the second retaining mechanism to translate within the samplehandling apparatus 400. In this way, the location of the first substrateand/or the second substrate can be controlled and adjusted such that thesample area of the first substrate can be aligned with the array area ofthe second substrate.

FIG. 26 is a process flow diagram illustrating an example process 2600for automatically determining a sample area indicator responsive todetermining an area of the sample according to some implementations ofthe current subject matter. At 2610, a data processor can determine anarea of the sample relative to an area of the array, such as duringalignment of the outline of the sample to the array area. For example,the data processor can be configured to determine an area of the samplerelative to an area of the array in an automated manner. In someembodiments, the sample substrate would be imaged first and an outlineof the sample could be determined using an image processing pipelineconfigured within the sample handling apparatus 400 or the dataprocessor. If the sample size is determined to be larger than arraysize, the image processing pipeline can annotate the target sample areawith an annotation detectable to the image processing pipeline.

In some embodiments, a user can manually align the outline of the sampleto the array area. When the outline is not clear, or the sample islarger, the sample substrate or slide can be annotated by an expertindicating the sample area on the sample substrate with a marker, astamp, a sticker, or the like. In some embodiments, the sample handlingapparatus 400 can apply the annotation based on user provided inputsidentifying the sample area or a region of interest in a display of thesample handling apparatus. In some embodiments, the inputs can beprovided to the sample handling apparatus 400 or to a computing devicecommunicatively coupled to the sample handling apparatus 400.

At 2620, the data processor can automatically determine a sample areaindicator on the first substrate responsive to determining the area ofthe sample is less than the area of the array. For example, after thesample substrate is imaged and the outline of the sample is determinedusing the image processing pipeline, the outline may be compared to thearea of the array to determine the area of the sample is less than thearea of the array.

At 2630, the data processor can provide the sample area indicator as anoutline of the sample. For example, the sample area indicator can beprovided in a display of the computing device.

At 2640, the data processor can perform the adjusting automaticallybased on the outline of the sample. For example, the data processor canuse the image processing pipeline of the sample handling apparatus 400to fit the outline within the array area. The sample handling apparatus400 can be configured to provide the actuation to cause the alignmentvia one or more actuators. In some embodiments, the alignment could beto the array itself, to a virtual outline provided in a graphical userinterface of a display of the sample handling apparatus 400, or toalignment reference marks provided in the sample handling apparatus thatindicate where the array will be located. As described above, the dataprocessor of the computing device can be configured to automaticallyadjust the location of the first substrate relative to the secondsubstrate to cause all or a portion of the sample area to be alignedwith an array area of the second substrate via a controller that can becommunicatively coupled to the sample handling apparatus 400 and to thecomputing device. The controller can receive input signals from the dataprocessor and can generate control signals causing the first retainingmechanism or the second retaining mechanism to translate within thesample handling apparatus 400 and there by adjust the location of thefirst substrate or the second substrate, respectively.

FIG. 27 is a process flow diagram illustrating an example process 2700for determining a fiducial mark located on a first substrate accordingto some implementations of the current subject matter. At 2710, a dataprocessor can determine a fiducial mark located on the first substrate.The fiducial marks can be determined using computer vision and/or imageprocessing functionality provided in an image processing pipelineconfigured within the sample handling apparatus 400. The fiducial mayinclude a high contrast or uniquely shaped mark to aid in determinationof the fiducial via the computer vision and/or image processingfunctionality provided in an image processing pipeline, or othermethods.

At 2720, the data processor can perform the adjusting automaticallybased on the determined fiducial mark. As described above, the dataprocessor of the computing device can be configured to automaticallyadjust the location of the first substrate relative to the secondsubstrate to cause all or a portion of the sample area to be alignedwith an array area of the second substrate via a controller that can becommunicatively coupled to the sample handling apparatus 400 and to thecomputing device. In some aspects, the adjusting may be based on thelocation of the determined fiducial. For example, the fiducial mayprovide a reference point for aligning the first substrate with thesecond substrate. The controller can receive input signals from the dataprocessor and can generate control signals causing the first retainingmechanism or the second retaining mechanism to translate within thesample handling apparatus 400 and there by adjust the location of thefirst substrate or the second substrate, respectively.

FIG. 28 is a process flow diagram illustrating an example process 2800for identifying a sample area indicator based on a registered sampleimage according to some implementations of the current subject matter.At 2810, a data processor of a first computing device can receive animage of a sample and a sample area indicator from a second computingdevice communicatively coupled to the first computing device.

At 2820, the data processor of the first computing device can registerthe receive image of the sample and the sample area indicator with atleast on video image of a plurality of video images. The plurality ofvideo images can be acquired via an image capture device 1720, such as amicroscope, a camera, an optical sensor, an imaging device, or the like,communicatively coupled to the data processor of the first computingdevice.

At 2830, the data processor of the first computing device can provide,based on the image registration, a registered sample image via a displayof the first computing device. For example, the registered sample imagecan be provided in a display of the first computing device.

At 2840, an input identifying the sample area indicator in theregistered sample image can be received at the first computing device.For example, a user can provide an input to a GUI provided in a displayof the first computing device. In some embodiments, the display canreceive the input directly from the user or via an input device, such asa mouse or a stylus, coupled to the display.

At 2850, the data processor can perform the adjusting automaticallybased on the received input identifying the sample area indicator. Thecomputing device can be configured to automatically adjust the locationof the first substrate relative to the second substrate to cause all ora portion of the sample area to be aligned with an array area of thesecond substrate via a controller that can be communicatively coupled tothe sample handling apparatus 400 and to the first computing device. Thecontroller can receive input signals from the data processor and cangenerate control signals causing the first retaining mechanism or thesecond retaining mechanism to translate within the sample handlingapparatus 400 and there by adjust the location of the first substrate orthe second substrate, respectively.

FIGS. 29A-29C depict a workflow 2900 for permeabilization of a sample(e.g., sample 302) of the sample handling apparatus 400. FIGS. 29A-29Care similar to and adapted from FIGS. 18A-18C and the workflow 2900 mayoccur after the workflow 1800. In some embodiments, the workflow 2900can occur after one or more of process 1900 described in relation toFIG. 19 , process 2300 described in relation to FIG. 23 , process 2500described in relation to FIG. 25 , process 2700 described in relation toFIG. 27 , and process 2800 described in relation to FIG. 28 .

After alignment of the slides 303 and 304 (e.g., as shown in FIG. 18C),a permeabilization solution (e.g., permeabilization solution 305) may beadded. The permeabilization solution 305 may create a permeabilizationbuffer in the sandwich (e.g., within the gap 307) which permeabilizes ordigests the tissue sample (e.g., sample 302). The analytes and/or mRNAtranscripts of the tissue sample 302 may release, diffuse across the gap307 toward the capture probes 306, and bind on the capture probes 306(e.g., as shown in FIG. 3 ).

As shown in FIG. 29A, after alignment of the slides 303 and 304, thesecond member 410 may be lowered to facilitate in adding thepermeabilization solution 305. In some embodiments, the alignment of theslides 303 and 304 may occur when second member 410 is in a loweredposition to facilitate in adding the permeabilization solution 304.

FIG. 29B depicts the permeabilization solution 305 dispensed on theslide 304. As shown, the permeabilization solution is dispensed in twovolumes 305A and 305B located in proximity to the capture probes 306Aand 306B, respectively. In some aspects, the permeabilization solution305 may be dispensed manually by a user or automatically via a componentof the sample handling apparatus 400.

FIG. 29C depicts a sandwich formed by the slide 303, the slide 304, andthe sample 302. During the sandwiching of the slides and sample, thepermeabilization solution 305 may begin to digest the sample 302 andrelease analytes and or mRNA transcripts of the sample 302 for captureby the capture probes 306A and 306B. In some aspects, the sandwich maybe formed by moving the second member 410 up towards the first members404A and 404B such that the sample 302 contacts at least a portion ofthe permeabilization solution 305 and the slides 303 and 304 are withina threshold distance along an axis orthogonal to the slides (e.g., alonga z axis). The movement of the second member 410 may be performed by anadjustment mechanism (e.g., the adjustment mechanism 415) of the samplehandling apparatus 400.

IV. Image Registration Devices and Methods

FIG. 30 is a diagram of an example sample handling apparatus 3000 inaccordance with some example implementations. The sample handlingapparatus 3000 is similar to and adapted from the sample handlingapparatus 400 of FIGS. 4-13C.

As shown, the sample handling apparatus 3000 includes an adjustmentmechanism 415, a linear guide 3016, an illumination source 3017 (e.g., atrans-illumination source), one or more heaters 1108, first members 404Aand 404B, tissue slides 303A and 303B, tissue samples 302A and 302B, agene expression slide 304, and the image capture device 1720. In theexample of FIG. 30 , the adjustment mechanism 415 is configured to moveone or more first members 404 along an axis orthogonal to the firstmembers 404 (e.g., along a z axis). The linear guide 3016 may aid in themovement of the one or more first members 404 along the axis. As furthershown, the image capture device 1720 may be mounted on a shuttle 3025configured to move the image capture device 1720 laterally from aposition inferior to the first member 404A to a position inferior to thefirst member 404B. The shuttle 3025 may allow the image capture device1720 to capture images of the tissues 302A and 302B aligned withportions of the gene expression slide 304. In some embodiments, a secondimage capture device 1720 can be provided within the sample handlingapparatus 400. Embodiments, including a second image capture device 1720may not include the shuttle 3025 and instead, the first and second imagecapture devices may be fixed within the sample holding apparatus 400 ina position suitable for capturing image data associated with tissuesample 302A and 302B, respectively. The illumination source 3017 (e.g.,trans-illumination source) may facilitate image capture of the alignedportions by providing sufficient illumination of the image capture area.In some embodiments, the illumination source 3017 can provide red light,green light, blue light, or combinations thereof.

In some embodiments, the illumination source 3017 can provide green, redor blue (e.g., RGB) illumination or light. The different illuminationcolors can be selected to prevent annotation marks from impacting theimage data processing and image registration methods described herein.For example, green light can be used for tissue segmentation with eosinstains and tissue contrast will be maximized. Annotation marks, such asthe regions of interest 1802 applied by a user, don't absorb green lightand thus the annotation marks will have a lower contrast when imagedunder green light.

In another example, red light can be used for fiducial detection witheosin stains and tissue contrast will be minimized. The fiducial framecan be visible in these conditions even when covered by tissue. Fiducialmarks don't absorb red light and thus the fiducial marks will have alower contrast when imaged under red light. In another example, bluelight can be used during array alignment since annotation marks absorbblue light and thus have a higher contrast. The use of blue light duringalignment can thus improve the accuracy of the alignment and results ofthe image registration methods.

FIGS. 31A-31C depict a workflow 3100 for image capture of the sandwichedslides of the sample handling apparatus 400 during a permeabilizationstep in accordance with some example implementations. FIGS. 31A-31C aresimilar to and adapted from FIGS. 29A-29C and the workflow 3100 mayoccur after the workflow 2900. In some embodiments, the workflow 3100can occur after one or more of process 1900 described in relation toFIG. 19 , process 2300 described in relation to FIG. 23 , process 2500described in relation to FIG. 25 , process 2700 described in relation toFIG. 27 , and process 2800 described in relation to FIG. 28 .

After adding the permeabilization solution (e.g., permeabilizationsolution 305) to the aligned slides, It may be beneficial to captureimages of the aligned tissue sample 302 and/or the barcoded captureprobes 306 to aid in mapping gene expressions to locations of the tissuesample 302. As such, the image capture device 1720 may be configured tocapture images of the aligned tissue sample 302, regions of interest1802, and/or the barcoded capture probes 306 during a permeabilizationstep.

FIG. 31A depicts the image capture device 1720 capturing a registrationimage of the aligned region of interest 1802A and the capture probes306A during permeabilization. The bottom portion of FIG. 31A shows anexample registration image 3121 captured by the image capture device1720 of the tissue sample 302A. As further shown, it may be desirablethat an alignment precision of the slides 303 and 304 be less than 10microns. The registration image 3121 may record alignment of anyfiducial's on the gene expression slide 304 with respect to the tissue302.

FIG. 31B depicts the image capture device 1720 capturing a secondregistration image of the aligned region of interest 1802B with thecapture probes 306B during permeabilization. The bottom portion of FIG.31B shows an example second registration image 3122 captured by theimage capture device 1720 of the tissue sample 302B.

In some aspects, the permeabilization step may occur within one minuteand it may be beneficial for the image capture device 1720 to movequickly between the different sandwiched slides and regions of interest.Although a single image capture device 1720 is shown, more than oneimage capture device 1720 may be implemented.

FIG. 31C depicts the sample handling apparatus 400 after anyregistration images (e.g., registration images 3121 and/or 3122) arecaptured and the permeabilization step may be completed. As shown, thesandwich may be opened and any of the slides 303 and 304 may be removedfor washing or a wash solution may be loaded into the instrument forwashing. For example, the gene expression slide 303 may be removed forwashing, library prep, gene sequencing, image registration, geneexpression mapping, or the like.

In some aspects, the sandwich may be opened by moving the second member410 away from the first members 404, or vice versa. The opening may beperformed by the adjustment mechanism 415 of the sample handlingapparatus 400.

While workflows 1700, 1800, 2900, and 3100 are shown and described withrespect to the sample handling apparatus 400, the workflows 1700, 1800,2900, and 3100 may also be performed with respect to the sample handlingapparatus 1400, the sample handling apparatus 3000, or another samplehandling apparatus in accordance with the implementations describedherein. In some embodiments, the processes 1900, 2300, 2500, 3000, 2700,and 2800 may also be performed with respect to the sample handlingapparatus 1400, the sample handling apparatus 3000, or another samplehandling apparatus in accordance with the implementations describedherein.

The spatialomic (e.g., spatial transcriptomic) processes and workflowsdescribed herein can be configured to display gene expressioninformation over high-resolution sample images. Barcoded locationswithin a reagent array can capture transcripts from a sample that is incontact with the array. The captured transcripts can be used insubsequent downstream processing. Determining the location of thebarcoded locations of the reagent array relative to the sample can beperformed using fiducial markers placed on a substrate on which thereagent array is located. The barcoded locations can be imaged with thesample to generate spatialomic (e.g., spatial transcriptomic) data forthe sample.

Generating image data suitable for spatialomic (e.g., spatialtranscriptomic) analysis can be affected by the relative alignment of asample with the barcoded regions of the reagent array. High-resolutionarrays for spatialomic (e.g., spatial transcriptomic) can requireresolution of the inferred barcoded locations overlaid atop ahigh-resolution sample image in order to properly associate the capturedtranscripts with the particular cell that the transcripts originatedfrom. The sample handling apparatus 400 can be configured to perform theimage registration processes and workflows described herein to provide alevel of precision for aligning the sample image and the array imagewithin +/−1-5 microns, +/−1-10 microns, +/−1-20 microns, or 1-30+/−microns.

FIG. 32 is a process flow diagram illustrating an example process 3200for generating an aligned image based on registering a sample image toan array image according to some implementations of the current subjectmatter. At 3210, sample image data can be received by a data processorof the sample handling apparatus 400. In some embodiments, the sampleimage data can be received by the data processor from a user. In someembodiments, the sample image data can be received by the data processorfrom a computing device that is remotely located relative to the dataprocessor.

The sample image data can include a sample image having a firstresolution. For example, the resolution of the sample image can be theoverall resolution of the image and can be based on the magnification,the numerical aperture, the resolution of the sensor or capture devicein megapixels, and wavelength. For example, a capture device, such asthe image capture device 1720 described in relation to FIGS. 17 and 30 ,can be configured to capture a sample image at a resolution of 0.8microns using a 10× objective, a 0.45 numerical aperture at a wavelengthof 575 nanometers. In some embodiments, the sample handling apparatus400 can be configured to capture a sample image having a firstresolution. For example, the sample apparatus 400 can be configured tocapture the sample image having the first resolution via ahigh-resolution imaging module configured for brightfield and/orfluorescence modalities. The high-resolution imaging module can includehigh-resolution magnification image capture devices. In someembodiments, the high-resolution imaging module can also include amotorized stage configured to translate along horizontal and verticalplanes (e.g., xy planes) so that multiple high-resolution images can becaptured to form a single large image. In some embodiments, the sampleimage having the first resolution can be captured by an imaging systemexternal to the sample handling apparatus 400 and prior to use of thesample handling apparatus 400. For example, a user may utilize a imagecapture device and/or system that is remote and external from the samplehandling apparatus 400 to capture the sample image prior to using thesample handling apparatus 400 to perform the spatialomic (e.g., spatialtranscriptomic) assay processes and workflows described herein. Thesample image captured remotely or externally in this manner can betransmitted to the data processor of the sample handling apparatus 400,where it can be received for further processing as described in relationto operation 3210.

At 3220, the data processor can receive array image data comprising anarray image. The array image can comprises an overlay of an array, suchas a reagent array configured with the barcoded locations, with thesample. The array image can also include an array fiducial. The arrayfiducial can be used to infer the location of the array and the barcodedlocations within the array so that coordinates of the barcoded locationscan be determined relative to the array fiducial. The array image canhave a second resolution lower than the first resolution of the sampleimage.

At 3230, the data processor can register the sample image to the arrayimage by aligning the sample image and the array image. The registeringcan be performed as an intensity-based image registration process usinga Matte's mutual information (entropy) or a mean differential metric.Preprocessing can be performed on the sample image and the array image.The preprocessing can include matching pixel-wise resolution(up-sampling), mirror image flipping, and angular rotation. An initialimage transformation can be generated based on an initial transform typeand an initial transformation matrix. The initial transformation matrixtype can include a similarity transformation matrix based ontranslation, rotation, and scale. In some embodiments, the initialtransformation matrix can include an affine transformation matrix basedon translation, rotation, scale, and shear. The initial imagetransformation can be processed with respect to an initial moving imageusing bilinear interpolation to generate a transformed moving image. Thetransformed moving image can be registered with a fixed image togenerate a registration metric, such as a measure of Matte's mutualinformation (entropy) or a mean differential metric value. The resultcan be provided to an optimizer for comparison against predeterminedthreshold values. Based on the comparison, the registration can continueusing a new transformation matrix or can be completed to generate analigned, registered image. In some embodiments, the sample image canfurther include a sample fiducial and the registering can furtherinclude aligning the array fiducial with the sample fiducial.

At 3240, the data processor, can generate the aligned image based on theregistering performed at 3230. The aligned image can include an overlayof the sample image with the array. In some embodiments, the alignedimage can include the array fiducial aligned with the sample.

At 3250, the data processor can provide the aligned image. For example,aligned image can be provided via a display of the sample handlingapparatus 400, 1400, or 3000 described herein.

FIGS. 33A-33E depict a workflow 3300 for registering a sample image toan array image according to some implementations of the current subjectmatter. The image registration processes and workflows described hereincan be enhanced by aligning a sample on a first substrate with a reagentarray on a second substrate. To perform the aligning and imageregistration, the coordinates of the barcoded locations within thereagent array and the size of the barcoded reagent locations can beprovided. In some embodiments, the coordinates of the barcoded locationsand the size of the barcoded locations can be provided by themanufacturer of the substrate on which the reagent array is configured.In some embodiments, the coordinates of the barcoded locations and thesize of the barcoded locations can be imaged and provided by themanufacturer of the sample handling apparatus 400, 1400, and 3000. Insome embodiments, the coordinates of the barcoded locations and the sizeof the barcoded locations can be imaged and provided by a user of thesample handling apparatus 400, 1400, and 3000 prior to performingspatialomic (e.g., spatial transcriptomic) assays. To further performthe aligning and image registration, a high-resolution brightfield orfluorescence image of the sample can be provided. The high-resolutionbrightfield image can be registered to a lower resolution imagecomprising an overlay of the barcoded locations with the sample.

As shown in FIG. 33A, a substrate or slide can be provided and caninclude an array fiducial 3305 and an array of barcoded locations 3310.The array fiducial 3305 can be a micro-scale stamp or sticker withfeatures dimensioned in microns. The diameter of the barcoded locations3310 can be between 40-60 microns, such as 55 microns. In someembodiments, the diameter of the barcoded locations 3310 is less than 40microns, e.g., less than 10 microns, e.g., around 5 microns. In FIG.33B, a substrate or slide can be provided including a sample 3315. Auser can provide the sample on the substrate. The sample can be providedat any location on the substrate. In FIG. 33C, a high-resolution imageof the sample 3315 can be captured via an image capture device. Thehigh-resolution image can typically include an image suitable forresolving subcellular histological and pathological features. Thehigh-resolution image can include images having a resolution less than5-10 microns. The image capture device can be configured to captureimages at a resolution between 1000 and 3000 pixels. In FIG. 33D, thesample substrate can be brought into contact with the array substratewithin the sample handling apparatus 400, 1400, and 3000 and alow-resolution image can be captured by the image capture device 1720.The low-resolution image can include an overlay of the array of barcodedlocations 3310 and the sample 3315. The low-resolution image can alsoinclude the array fiducial 3305. The low-resolution image can include animage that has a lower resolution than the high-resolution imagedescribed above (e.g., an image having a resolution greater than 5-10microns). In FIG. 33E, image registration can be performed between thehigh-resolution image of the sample 3315 shown in FIG. 33C and the lowerresolution image of the overlay of the array of the barcoded locations3310 and the sample 3315. The image registration can align the arrayfiducial 3305, such as the center of the array fiducial 3305, with thelow-resolution image acquired in FIG. 33D, and the high-resolution imageacquired in FIG. 33C can be aligned to the low-resolution image acquiredin FIG. 33D to generate the overlay of barcoded locations 3310 displayedover the high-resolution image captured in FIG. 33C.

FIGS. 34A-34E depict a workflow 3400 for registering a sample image toan array image based on aligning a sample fiducial and an array fiducialaccording to some implementations of the current subject matter. In someembodiments, the manufacturer of the sample handling apparatus 400,1400, and 3000 can provide a sample substrate or slide in addition tothe array substrate on which an array fiducial and barcoded locationsare provided. For example, as shown in FIG. 34A, the array substrate caninclude an array fiducial 3405 and barcoded locations 3410. In FIG. 34B,the sample substrate or slide can include a sample fiducial 3415 and asample area indicator 3420. In FIG. 34C, a user can provide a sample3425 onto the substrate within the sample area defined by the samplearea indicator 3420. In FIG. 34D, an image capture device can acquire ahigh-resolution image of the sample 3425 and the sample fiducial 3415.In some embodiments, the high-resolution image can be acquired prior tothe sample substrate being received within the sample handling apparatus400, 1400, and 3000. Once the sample substrate is received, the samplesubstrate and the array substrate can be brought into contact within thesample handling apparatus 400, 1400, and 3000 and the image capturedevice 1720 can acquire a low-resolution image including the arrayfiducial 3405 aligned with the sample fiducial 3415 as shown in FIG.34E. The alignment of the array fiducial 3405 with the sample fiducial3415 can be used to generate an overlay of the array 3430 of barcodedlocations 3410 atop the high-resolution image of the sample captured inFIG. 34D.

FIGS. 35A-35E depict a workflow 3500 for registering a sample image toan array image based on aligning a user-provided or system-providedsample fiducial and an array fiducial according to some implementationsof the current subject matter. In some embodiments, the user of thesample handling apparatus 400, 1400, and 3000 or the sample handlingapparatus itself can provide a sample fiducial on a substrate or slideintended for use as a sample substrate or slide. In such embodiments,any substrate or slide can be used as the sample substrate or slide foralignment and image registration. For example, as shown in FIG. 35A, thearray substrate can include an array fiducial 3505 and barcodedlocations 3510. In FIG. 35B, a user can provide a sample substrate orslide and the sample 3515 can be placed anywhere on the user-providedsample substrate or slide. In FIG. 35C, users or the sample handlingapparatus 400, 1400, and 3000 can provide a sample fiducial 3520 and/ora sample area indicator 3525 to the user-provided sample substrate orslide on which the sample 3515 was placed. In some embodiments, theuser-provided sample fiducial 3520 and/or the user-provided sample areaindicator 3525 can include a stamp or a sticker applied to the samplesubstrate or slide. In some embodiments, the sample fiducial 3520 and/orthe user-provided sample area indicator 3525 can be a mark on the samplehandling instrument 400, 1400, and 3000. The mark on the instrument canbe a high contrast mark including affordances to easily identify thecenter of the mark. In 35D, a high-resolution image of the sample 3515,the sample fiducial 3520, and the sample area indicator 3525 (ifprovided) can be acquired using the image capture device. In someembodiments, the high-resolution image can be acquired prior to thesample substrate being received within the sample handling apparatus400, 1400, and 3000. The sample substrate and the array substrate can bebrought into contact within the sample handling apparatus 400, 1400, and3000 and the image capture device 1720 can acquire a low-resolutionimage including the array fiducial 3505 aligned with the sample fiducial3520 as shown in FIG. 35E. The alignment of the array fiducial 3505 withthe sample fiducial 3520 can be used to generate an overlay of the array3530 of barcoded locations 3510 atop the high-resolution image of thesample captured in FIG. 34D.

FIGS. 36A-36B depict a workflow 3600 for registering a sample image toan array image based on aligning an edge of a sample substrate and anarray fiducial according to some implementations of the current subjectmatter. In some embodiments, the alignment and image registration can beperformed using an edge of a user-provided substrate or slide as thesample fiducial. In such embodiments, any substrate or slide can be usedas the sample substrate or slide for alignment and image registration.For example, as shown in FIG. 36A, a sample 3610 can be placed at anylocation on a substrate or slide. An edge 3605 of the substrate or slidecan be used as a sample fiducial. A high-resolution image of the sampleand the edge 3605 can be captured via the image capture device In someembodiments, the high-resolution image can be acquired prior to thesample substrate being received within the sample handling apparatus400, 1400, and 3000. In some embodiments, the high-resolution image canbe acquired using macros or image acquisition/processing softwareconfigured to capture the edge 3605 within the high-resolution image.Once the sample substrate is received, the sample substrate and thearray substrate can be brought into contact within the sample handlingapparatus 400, 1400, and 3000 and the image capture device 1720 canacquire a low-resolution image including the array fiducial 3615 alignedwith the edge 3605 as shown in FIG. 36B. The alignment of the arrayfiducial 3615 with the edge 3605 as the sample fiducial can be used togenerate an overlay of the array 3620 of barcoded locations atop thehigh-resolution image of the sample captured in FIG. 36A.

FIGS. 37A-37D are diagrams illustrating embodiments of sample fiducialsaccording to some implementations of the current subject matter. Avariety of non-limiting sample fiducial and sample area indicator sizes,shapes, and configurations can be contemplated for use with the samplehandling apparatus 400, 1400, and 3000 without deviating from theintended use of the sample fiducial and/or sample area indicatorsdescribed herein. The varying sizes, shapes, and configurations ofsample fiducials and/or sample area indicators can be provided toaccommodate varying sizes of samples. For example, as shown in FIG. 37A,the sample fiducial 3705A can be positioned relative to a sample areaindicator 3710 provided as a square-shaped dashed line. In someembodiments, multiple sample fiducials can be provided on the samplesubstrate or slide as shown by the inclusion of a second sample fiducial3705B. In some embodiments, the sample area indicator 3710 can include asquare shape, a rectangular shape, a circular shape, an oval shape, orthe like. The sample fiducial 3705 can be positioned in a variety ofnon-limiting locations in or around the sample area indicator 3710. Asshown in FIG. 37B, the shape of the sample area indicator 3710 can be arectangular shaped dashed line. As shown in FIG. 37C, the samplefiducial 3720 can be configured within the sample area indicator 3725.The sample area indicator 3725 can include a square shape provided as athick solid line. In FIG. 37D, the sample area indicator 3730 can beprovided as a rectangular shaped solid line and the sample fiducial 3720can be provided within the sample area indicator 3730.

FIGS. 38A-38C are diagrams illustrating embodiments of a sample fiducialconfigured on a rear of a sample substrate according to someimplementations of the current subject matter. Providing a samplefiducial on a rear surface of a sample substrate or slide can allow thesample fiducial to be placed anywhere on the sample substrate or slide,including a location that is within a location of the sample. Forexample, as shown in FIG. 38A, a sample substrate or slide can beprovided and a sample 3805 can be placed on a surface of the substrate.In FIG. 38B, a sample fiducial 3810 can be placed on an opposite surfaceof the sample substrate on which the sample 3805 was applied in FIG.38A. In FIG. 38C, a cross-section of the sample substrate or slide canbe seen to further indicate the placement of the sample 3805 on a tissueor sample side of the sample substrate and the placement of the samplefiducial 3810 on a fiducial side of the sample substrate or slide. Thefiducial side can be opposite to the tissue or sample side of thesubstrate or slide on which the sample 3805 is located.

An image capture device of the sample handling apparatus 400, 1400, and3000 can be configured for capturing high-resolution images such that asample substrate image and an array substrate image can be captured attwo different focal points while keeping the xy location fixed. Tocapture the sample and the sample fiducial in the low-resolution imagewith the same focus, the image capture device 1720 can be configuredwith a low magnification object lens with a numerical aperture set to0.02. This setting can provide a 1.5 mm field depth that is greater thana thickness of the sample substrate or slide (˜1 mm). In someembodiments, the sample fiducial 3810 can be an opaque or transparentfiducial, such as when the high-resolution image is captured priorcontacting the sample substrate with the array substrate within thesample handling apparatus 400, 1400, and 3000.

FIGS. 39A-39E are diagrams illustrating embodiments of configurations ofarray fiducials according to some implementations of the current subjectmatter. Similar to the placement of the sample fiducial on the samplesubstrate or slide, an array fiducial can be provided in a variety ofnon-limiting locations on the array substrate or slide without deviatingfrom intended use of the array fiducial and/or the array as describedherein. For example, as shown in FIG. 39A, an array substrate or slidecan include an array fiducial 3905 located relative to the array 3910 ofbarcoded locations. The array fiducial 3905 can be located next to or inproximity of the array 3910. As shown in FIG. 39B, the array fiducial3905 can be located within an area of the array 3910. As shown in FIG.39C, multiple array fiducials 3905A and 3905B can be located on thearray substrate or slide next to or in proximity of the array 3910. Insome embodiments, multiple array fiducials 3905 can be located within anarea of the array 3910. As shown in FIG. 39D, the array fiducial 3905can be located on a rear surface of the array substrate or slide that isopposite the side on which the array 3910 is located. As shown in FIG.39E, the array fiducial 3905 can be located on the same side of thearray substrate or slide as the array 3910.

FIGS. 40A-40C are diagrams illustrating embodiments of locations atwhich a low-resolution image including an array overlaid atop a samplecan be captured for registering a sample image to an array imageaccording to some implementations of the current subject matter. Thelow-resolution image described in relation to operation 3220 of FIG. 32by the image capture device 1720 can be captured on, near, or away froman area in which the sample and the array overlap depending on thelocation of the sample fiducial and the array fiducial. For example, asshown in FIG. 40A, the low-resolution image can be captured by the imagecapture device 1720 at a location 4005 in which at least a portion ofthe sample 4010 and the array 4015 overlap. As shown in FIG. 40B, thelow-resolution image can be captures by the image capture device 1720 ata location 4020 in which the sample 4010 and the array 4015 overlap morecompletely. As shown in FIG. 40C, the low-resolution image can becaptured by the image capture device 1720 at a location 4025 in whichthe array fiducial 4030 is aligned with or is in proximity of the samplefiducial 4035.

FIG. 41 is a process flow diagram illustrating an example process 4100for generating an aligned image based on registering a sample image toan array image using multiple instrument fiducials according to someimplementations of the current subject matter. In some embodiments, suchas those described in relation to FIG. 21 , the sample handlingapparatus 400, 1400, and 3000 can include one or more instrumentfiducials. The instrument fiducials can be provided on a transparentsurface of the sample handling apparatus described herein. Imageregistration can be performed to provide an aligned image including thesample aligned with the array using the instrument fiducials.

At 4110, a data processor of the sample handling apparatus 400, 1400,and 3000 can receive sample image data comprising a sample image of asample and a sample fiducial. The same image can have a firstresolution. The sample image data can be received in accordance withoperation 3210 of FIG. 32 . At 4120, the data processor can receiveinstrument fiducial data comprising an instrument fiducial image of afirst instrument fiducial and a second instrument fiducial. Theinstrument fiducials can include a variety of non-limiting sizes,shapes, and configurations on a suitable mounting or viewing surface ofthe sample handling apparatus 400, 1400, and 3000 as described inrelation to FIG. 30 .

At 4130, the data processor can receive array image data comprising anarray image having a second resolution that is lower than the firstresolution of the sample image. The array image can include an array andan array fiducial overlaid atop the sample and the sample fiducial. Thearray image data can be received in accordance with operation 3220 ofFIG. 32 . At 4140, the data processor can register the instrumentfiducial image to the array image based on aligning the first instrumentfiducial and the array fiducial. The registering can be performedanalogously to the registering described in relation to operation 3230of FIG. 32 , except the registration is performed by registering theinstrument fiducial image to the array image based on aligning the firstinstrument fiducial and the array fiducial. At 4150, the data processorcan register the instrument fiducial image to the sample image byaligning the second instrument fiducial and the sample fiducial. Theregistering can be performed analogously to the registering described inrelation to operation 3230 of FIG. 32 , except the registration isperformed by registering the instrument fiducial image to the sampleimage based on aligning the second instrument fiducial and the samplefiducial.

At 4160, the data processor can generate an aligned image based onregistering the instrument fiducial image to the array image andregistering the instrument fiducial to the sample image. At 4170, thedata processor can provide the aligned image. For example, the dataprocessor can provide the aligned image via a display of the samplehandling apparatus 400, 1400, and 3000.

FIGS. 42A-42D depict a workflow 4200 for generating an aligned imagebased on registering a sample image to an array image using multipleinstrument fiducials according to some implementations of the currentsubject matter. As shown in FIG. 42A, the sample handling apparatus 400,1400, and 3000 can include a transparent viewing or mounting surface4205 configured with a first instrument fiducial 4210 and a secondinstrument fiducial 4215. As shown in FIG. 42B, an array substrate orslide can include an array fiducial 4220 and an array 4225. As shown inFIG. 42C, a sample substrate or slide can include a sample fiducial 4230and a sample 4235. As shown in FIG. 42D, the array substrate includingthe array fiducial 4220 can be aligned with the first instrumentfiducial 4210 and the sample fiducial 4230 can be aligned with thesecond instrument fiducial 4215. The sample substrate and the arraysubstrate can be brought into contact within the sample handlingapparatus 400, 1400, and 3000 and the image capture device 1720 canacquire multiple low-resolution images. A first low-resolution image canbe captured based on aligning the first instrument fiducial 4210 to thearray fiducial 4220. A second low-resolution image can be captured basedon aligning the second instrument fiducial 4215 to the sample fiducial4230. The known coordinates of the barcoded locations within the array4225 relative to the array fiducial 4225, the known location of thesample 4235 relative to the sample fiducial 4230, and the known locationof the first instrument fiducial 4210 relative to the second instrumentfiducial 4215 can be used with the sample image received at operation4110 of FIG. 41 and the array image received at operation 4130 of FIG.41 to align the array 4225 with the sample 4235.

The sample handling apparatus 400, 1400, and 3000 described herein canbe configured to perform image registrations for sample images includingmultiple sample portion images which can be stitched together. When thehigh-resolution image of the sample is collected at a highmagnification, it is typically obtained using image stitching ofmultiple fields of view of the sample. Image stitching can result institching artifacts. The stitching artifacts can generate errors duringimage registration when aligning the lower resolution image, which canbe an unstitched lower resolution image of the array overlaid atop thesample, and the higher resolution stitched image of the sample.

FIGS. 43A-43B illustrate stitching artifacts which can be present withinstitched images including a plurality of individual image portions.Stitching artifacts can be present in high-resolution sample imagesincluding a plurality of sample portion images, and can also be presentin low-resolution array images including a plurality of array portionimages capturing one or more portions of an overlay of an array with thesample. The stitching artifacts can be present for horizontal, vertical,and curved features present within a stitched high-resolution image. Asshown in FIG. 43A, a stitched high-resolution image 4305 can be acquiredof an optical target 4310 of repeated patterns of a different shapedoptical target marks, such as small and large circular-shaped marks,cross-shaped marks, and hash-shaped marks. For example, the stitchedhigh-resolution image 4305 can be acquired at 10× magnification using animage capture device, such as a microscope, configured with a 150megapixel resolution. Imaging functionality associated with themicroscope can automatically stitch images together to build a largercomposite image (e.g., image 4305). As shown in FIG. 43A, the stitchedhigh-resolution image 4305 can include a single array that is 9 mm by 9mm in size and is comprised of 81 individual portion images that areeach 1 mm by 1 mm in size. The stitched high-resolution sample image4305 can include the template marks of the stitched optical target 4310.As shown in 4315, the stitching artifacts can include verticalmisalignment of a first cross-shaped template mark occurring across ahorizontal stitching boundary between two of the individual portionimages that the cross-shaped template mark spans. As shown in 4320, thestitching artifacts can include horizontal misalignment of thecross-shaped template mark occurring across a vertical stitchingboundary between two of the individual portion images that a secondcross-shaped template mark spans. As shown in 4315, the stitchingartifacts can include misalignment of a curved feature of a smallcircular-shaped template mark occurring across a horizontal stitchingboundary between two of the individual portion images that the smallcircular-shaped template mark spans.

As shown in 4330 of FIG. 43B, the stitching artifacts can includemisalignment of a curved feature of a large circular-shaped templatemark occurring across a horizontal stitching boundary between two of theindividual portion images that the large circular-shaped template markspans. As shown in 4335, the stitching artifacts can includemisalignment of a curved feature of a small circular-shaped templatemark occurring at an intersectional boundary of four individual portionimages. As shown in 4340, the stitching artifacts can includemisalignment of a curved feature of a small circular-shaped templatemark occurring near an intersectional boundary of four individualportion images

To mitigate and correct the image registration errors due to thestitching artifacts, the image registration can be performed usingportions of the high-resolution sample image and registering theportions of the sample image to the whole lower resolution image. Thestitching errors can also cause local registration errors. To mitigateand correct the local stitching errors, the image registration processesand workflows described herein can be performed using local sub imagesof the high-resolution stitched image. In this way, registration errorsdue to stitching artifacts can be mitigated and removed.

FIG. 44 is a process flow diagram illustrating an example process 4400for registering sample portion images of a sample image to correspondingportions of the sample in an array image according to someimplementations of the current subject matter. In some embodiments, thehigh-resolution sample image can include multiple sample portion imagesthat are stitched together to form the sample image. Each of the sampleportion images can be associated with a portion of the sample. In someembodiments, each of the sample portion images can be sized such thatthe size of each sample portion image is less than a size of a singlefield of view of the sample image. In this way, the locationregistration errors due to stitching artifacts can be corrected.

As shown in FIG. 44 , at 4410 the data processor of the sample handlingapparatus 400, 1400, and 3000 can crop the high-resolution sample imageto determine a plurality of sample portion images. The high-resolutionsample image can be cropped to determine the plurality of sample portionimages using computer vision and/or image processing functionalityprovided in an image processing pipeline configured within the samplehandling apparatus 400, 1400, and 3000. At 4420, the data processor canregister one or more of the sample portion images in the high-resolutionsample image to a corresponding portion of the sample in thelow-resolution array image. In some embodiments, registering the one ormore sample portion images to a corresponding portion of the sample inthe array image can be performed after initially registering the sampleimage to the array image in a pre-alignment operation.

FIG. 45 depicts a workflow 4500 for registering sample portion images ofa sample image to corresponding portions of the sample in an array imageaccording to some implementations of the current subject matter. Ahigh-resolution stitched sample image 4405 can be received by a dataprocessor of the sample handling apparatus 400, 1400, and 3000, such asthe data processor 5320 described in relation to FIG. 53 . In someembodiments, the data processor can be remote from or external to thesample handing apparatus 400, 1400, and 3000 and can be configured withthe image processing pipelines and functionality described herein. Insuch embodiments, image data captured using the sample handlingapparatus can be provided to the remote or externally configured dataprocessor via a USB or network connection. In some embodiments, thehigh-resolution stitched sample image 4505 can include an overlay of thearray with the sample and an array fiducial. A low-resolution sampleimage 4510 including a single field of view of the sample can also bereceived by the data processor of the sample handling apparatus 400,1400, and 3000. An initial alignment image 4515 can be generated via aglobal whole image registration operation registering thehigh-resolution stitched sample image 4505 to the lower resolutionsample image. In some embodiments, it may not be necessary to generatethe initial alignment image 4515. In some embodiments, prior togenerating the initial alignment image 4515, the sample substrate andthe array substrate can be aligned manually or automatically by the dataprocessor of the sample handling apparatus 400, 1400, and 3000. Thispreliminary alignment can be performed to specify the startingconditions of the image registration methods described herein.

The high-resolution stitched sample image 4505 can be cropped todetermine a plurality of sample portion images 4520. The plurality ofsample portion images 4520 can be locally registered with thelow-resolution sample image 4510 to generate an locally aligned sampleimage 4525. Each sample portion image of the plurality of sample portionimages can be smaller than a single field of view of the high-resolutionstitched sample image 4505. In this way, local registration errors dueto stitching artifacts can be corrected.

FIG. 46 is a process flow diagram illustrating an example process 4600for registering array portion images of an array image to correspondingportions of the sample in a sample image according to someimplementations of the current subject matter. In some embodiments, thelow-resolution image of the array overlaid atop the sample described inrelation to operation 3230 of FIG. 32 can include a plurality of arrayportion images. At 4610, the data processor of the sample handlingapparatus 400, 1400, and 3000 can determine a plurality of array portionimages in the low-resolution image of the array. The plurality of arrayportion images in the low-resolution image of the array can bedetermined using computer vision and/or image processing functionalityprovided in an image processing pipeline configured within the samplehandling apparatus 400, 1400, and 3000. At 4620, the data processor canregister one or more of the array portion images in the low-resolutionarray image to a corresponding portion of the sample in thehigh-resolution sample image.

FIG. 47 depicts a workflow 4700 for registering array portion images ofan array image to corresponding portions of the sample in a sample imageaccording to some implementations of the current subject matter. Ahigh-resolution stitched sample image 4705 can be received by a dataprocessor of the sample handling apparatus 400, 1400, and 3000. Alow-resolution array image 4710 including a single field of view of thearray overlaid atop the sample can also be received by the dataprocessor of the sample handling apparatus 400, 1400, and 3000. In someembodiments, the sample and the array can be located on a singlesubstrate or slide. An initial alignment image 4715 can be generated viaa global whole image registration operation registering thehigh-resolution stitched sample image 4705 to the lower resolution arrayimage. In some embodiments, it may not be necessary to generate theinitial alignment image 4715. In some embodiments, prior to generatingthe initial alignment image 4715, the sample substrate and the arraysubstrate can be aligned manually or automatically by the data processorof the sample handling apparatus 400, 1400, and 3000. This preliminaryalignment can be performed to specify the starting conditions of theimage registration methods described herein.

The low-resolution array image 4710 can be processed to determine aplurality of array portion images 4720. The plurality of array portionimages 4720 can be locally registered with the high-resolution stitchedsample image 4705 to generate an locally aligned sample image 4725. Eacharray portion image of the plurality of array portion images can besmaller than a single field of view of the high-resolution stitchedarray image 4675. In this way, local registration errors due tostitching artifacts can be corrected.

High resolution arrays for spatialomic (e.g., spatial transcriptomic)can be configured to identify 5-10 micron features and single cellresolution. The alignment of the inferred barcoded locations of thearray over the high-resolution sample image may require single cellresolution in order to properly associate the transcripts captured atthe barcoded locations with the cell from which the transcriptsoriginated. Typically the high-resolution sample image is acquired at ahigh magnification and can be stitched together using multiple fields ofview. This manner of stitching images together can generate stitchingartifacts. The stitching artifacts can cause errors when extrapolatingthe barcoded locations using fiducials. The stitching errors can be onthe order of 5-10 microns. If left uncorrected, the gene expression datawill be associated with the wrong location in the high-resolution sampleimage.

To correct or mitigate registration errors due to stitching artifacts, asingle field of view low-resolution sample image can be captured inaddition to the high-resolution sample image. The lower resolutionsample image may not include stitching artifacts. Thus, no spot locationerrors may arise when extrapolating the barcoded locations usingfiducials. Image registration can be performed between thehigh-resolution stitched sample image and the low-resolution unstitchedsample image using portions of the high-resolution stitched sampleimage. In this way, errors associated with the barcoded locations due tostitching artifacts can be mitigated and/or removed.

FIG. 48 is a process flow diagram illustrating an example process 4800for registering stitched sample portion images to corresponding portionsof the sample in a sample image according to some implementations of thecurrent subject matter. At 4810, the data processor of the samplehandling apparatus 400, 1400, and 3000 can receive a first sample imagedataset including a first plurality of sample portion imagescorresponding to portions of a sample. Each of the sample portion imagescan have a first resolution.

At 4820, the data processor can receive a second sample image datasetincluding a sample image of the sample. The sample image can have asecond resolution that is lower than the first resolution of each of thesample portion images in the first sample image dataset.

At 4830, the data processor can register one or more of the sampleportion images to a corresponding portion of the sample in the sampleimage.

FIG. 49 is a process flow diagram illustrating an example process 4900for registering stitched sample portion images to corresponding portionsof the sample in a sample image based on determining one or morebarcoded locations of an array in according to some implementations ofthe current subject matter. In some embodiments, the sample image caninclude a plurality of sample portion images that are individuallyassociated with a portion of the sample. In such embodiments, theregistering can further include operations of the process 4900 shown inFIG. 49 . For example, at 4910, the data processor can receive an arrayimage dataset including an array image of a single field of view of anarray. The array image can also include an array fiducial. At 4920, thedata processor can determine the array fiducial are within a singlefield of view of the array image. The array fiducials can be determinedusing the computer vision and/or image processing functionality providedin an image processing pipeline configured within the sample handlingapparatus 400, 1400, and 3000. In some embodiments, the array fiducialscan be pre-defined and can be visible under field of view. The user orsoftware can determine if all of the fiducial features are included inthe field of view before the image is taken. In some embodiments, thearray fiducials within a single field of view of the array image can bedetermined using computer vision and/or image processing functionalityprovided in an image processing pipeline configured within the samplehandling apparatus 400, 1400, and 3000. At 4930, the data processordetermines one or more barcoded locations of the array using the arrayimage. The generated aligned image, described in relation to operation3240 of FIG. 32 , can include the one or more barcoded locations.

FIG. 50 depicts a workflow 5000 for registering stitched sample portionimages to corresponding portions of the sample in a sample imageaccording to some implementations of the current subject matter. Ahigh-resolution stitched sample image 5005 including one or morefiducials 5010 can be received by the data processor of the samplehandling apparatus 400, 1400, and 3000. A single field of view,unstitched, low-resolution image 5015 including one or more fiducials5020 can also be received by the data processor of the sample handlingapparatus 400, 1400, and 3000. The fiducials 5020 and the sample 5025 inthe single field of view, unstitched, low-resolution image 5015 can beused to determine one or more barcoded locations 5030. Imageregistration can be performed between the single field of view,unstitched, low-resolution image 5015 and the high-resolution stitchedsample image 5005 to provide as shown in 5040 high-resolution barcodelocation information with respect to the high-resolution stitched sampleimage 5005.

FIG. 51 is a process flow diagram illustrating an example process 5100for registering stitched sample portion images to corresponding portionsof the sample in a sample image and registering stitched array portionimages to corresponding portions of the sample in the sample imageaccording to some implementations of the current subject matter. In someembodiments, the high-resolution stitched sample image can include aplurality of sample portion images. Each of the sample portion imagescan be associated with a corresponding portion of the sample. Thelow-resolution array image can include a plurality of stitched arrayportion images. Each of the array portion images can be associated witha corresponding portion of the array and can include a single field ofview.

At 5110, the data processor of the sample handling apparatus 400, 1400,and 3000 can determine a plurality of sample portion images in ahigh-resolution stitched sample image. The plurality of sample portionimages can be determined using computer vision and/or image processingfunctionality configured within or accessible via the data processor. Insome embodiments, the plurality of sample portion images can be knowninformation recorded by the image capture device when thehigh-resolution stitched sample image was taken. At 5120, the dataprocessor can register one or more of the sample portion images in thesample image to a corresponding portion of the sample in thelow-resolution stitched array image. At 5130, the data processor candetermine a plurality of array portion images in the low-resolutionstitched array image. The plurality of array portion images can bedetermined using computer vision and/or image processing functionalityconfigured within or accessible via the data processor. At 5140, thedata processor can register one or more array portion images in thelow-resolution stitched array image to a corresponding portion of thesample in the high-resolution stitched sample image.

FIG. 52 depicts a workflow 5200 for registering stitched sample portionimages to corresponding portions of the sample in a sample image andregistering stitched array portion images to corresponding portions ofthe sample in the sample image according to some implementations of thecurrent subject matter. A high-resolution stitched sample image 5205 canbe received by a data processor of the sample handling apparatus 400,1400, and 3000. The high-resolution stitched sample image 5205 caninclude one or more sample fiducials 5210. A low-resolution stitchedarray image 5215 including four single field of view array portionimages can also be received by the data processor of the sample handlingapparatus 400, 1400, and 3000. The low-resolution stitched array image5215 can include one or more array fiducials 5220. An initial alignmentimage 5225 can be generated via a global whole image registrationoperation registering the high-resolution stitched sample image 5205 tothe lower resolution stitched array image. In some embodiments, it maynot be necessary to generate the initial alignment image 5215. In someembodiments, prior to generating the initial alignment image 5225, thesample substrate and the array substrate can be aligned manually orautomatically by the data processor of the sample handling apparatus400, 1400, and 3000. This preliminary alignment can be performed tospecify the starting conditions of the image registration methodsdescribed herein.

A quarter of the low-resolution stitched sample image 5215 can beprocessed to determine a plurality of sample portion images 5230.Registration can be performed for each single field of view arrayportion images 5230. The fiducial 5235 can be used to facilitate mappingof the gene expression data to the high-resolution sample image. Sincethis quarter of the image 5215 can be a single field of view andunstitched, the location information between the tissue sample andfiducials can be determined to be accurate. The plurality of sampleportion images 5230 can be locally registered with the low-resolutionsingle field of view array image 5215 to generate a locally alignedsample image 5240. Each sample portion image of the plurality of arrayportion images can be smaller than a single field of view of thelow-resolution stitched sample image 5215. In this way, localregistration errors due to stitching artifacts in the high-resolutionimage can be corrected.

V. Image Registration System and Software Architecture

FIG. 53 is a diagram of an example system architecture 5300 forperforming the image registration processes and workflows describedherein in accordance with some example implementations. For example, thesystem architecture 5300 be configured to operate with the samplehandling apparatus 400, 1400, and 3000 to perform one or more ofworkflows and processes described herein. The system architecture 5300can also include a remote processing service 5355, a support portal5360, and a computing device 5365 that can be communicatively coupled toone another via a network 5350. The system architecture can beconfigured in a system and can perform image registration workflowsdescribed herein.

As shown in FIG. 53 , the sample handling apparatus 400, 1400, and 3000may include an input/output control board 5305 controlling operation ofmotors, pumps, fans, heaters, actuators, sensors, illuminations sources,fluid sources or the like that can be configured within the samplehandling apparatus 400, 1400, and 3000. A camera control 5310, and anetwork interface 5315 can also be included in the sample handlingapparatus 400, 1400, 3000. As shown, the input/output (I/O) controller5305, the camera control 5310, and the network interface 5315 may beconnected via a controller area network (CAN) bus. The camera control5310 may be configured to control aspects or components of a camera(e.g., the image capture device 1420 or 1720). For example, the cameracontrol 5310 may control a focus, a zoom, a position of the camera, animage capture, or the like.

The sample handling apparatus 400, 1400, and 3000 also includes aprocessor 5320, a memory 5325 storing one or more applications 5330, aninput device 5335, and a display 5340. The processor 5320 can beconfigured to execute computer-readable instructions stored the memory5325 to perform the workflows and processes associated with theapplications 5330. The processor 5320 can also execute computer-readableinstructions stored in the memory 5325, which cause the processor 5320to control operations of the sample handling apparatus 400, 1400, and3000 via the I/O controller 5305 and/or the image capture devices 1420,1720 via the camera control 5310. In this way, the processor 5320 cancontrol an operation of the sample handling apparatus 400, 1400, and3000 to align a sample with an array. For example, the processor 5320can execute instructions to cause either of the first retainingmechanism or the second retaining mechanism to translate within thesample handling apparatus 400, 1400, 3000 so as to adjust theirrespective locations and to cause a sample area of a first substrate tobe aligned with an array area of a second substrate.

The input device 5335 can include a mouse, a stylus, a touch-pad, a joystick, or the like configured to receive user inputs from a user. Forexample, a user can use the input device 5335 to provide an inputindicating a sample area indicator for a first substrate. The display5340 can include a graphical user interface 5345 displaying dataassociated with the one or more applications 5330.

The network interface 5315 may be configured to provide wired orwireless connectivity with a network 5350, such as the Internet, a localarea network, a wide area network, a virtual private network, a cellularnetwork or the like. In some embodiments, the network interface 5315 canbe configured to communicate via Ethernet, Wi-Fi, Bluetooth, USB, or thelike. The network 5350 may be connected to one or more distributedcomputing resources or remote processing services 5355. In someembodiments, the remote processing service 5355 can be a cloud computingenvironment, a software as a service (SaaS) pipeline. The remoteprocessing service 5355 can be configured to aid, perform, or controlautomated image alignment and/or image registration of the samplehandling apparatus 400, 1400, and 3000 described herein. The supportportal 5360 can be configured to send share image data, imageregistration data, instrument calibration data or self-test dataincluding images, videos, and logs or associated parameter data to thesupport portal 5655. In some embodiments, the remote processing service5355 or the support portal 5360 can be configured as a cloud computingenvironment, a virtual or containerized computing environment, and/or aweb-based microservices environment.

The sample handling apparatus 400 can also be communicatively coupledvia the network 5350 to a computing device 5365. In some embodiments,the second computing device 5365 can be located remotely from the samplehandling apparatus 400, 1400, and 3000.

The computing device 5365 can be configured to transmit and receive datawith the sample handling apparatus 400, 1400, and 3000. The computingdevice 5365 can include a desktop, laptop, mobile, tablet, touch-screencomputing device or the like. In some embodiments, the computing device5365 can include a smart phone, such as a phone configured with an iOSor Android operating system.

FIG. 54 is a diagram of an example software architecture 5400 forperforming the processes and workflows described herein in accordancewith some example implementations. The architecture 5400 can beconfigured in the memory 5325 of the sample handling apparatus 400,1400, and 3000 described in relation to FIG. 53 . Programmatic modulesof the architecture can be implemented as an operating system 5410(e.g., a Linux OS) of the sample handling apparatus 400, 1400, and 3000and can be stored in memory 5325. The operating system 5410 may includethe I/O controller 5305, a CAN driver 5412, a camera interface 5414, animage management subsystem 5420, a diagnostic subsystem 5425, astatistics collector 5430, a publication and subscription service 5435,and upgrade subsystem 5440, a platform management subsystem 5445, a userinterface subsystem 5450, a cloud management subsystem 5460, and anassay control subsystem 5470. The user interface subsystem 5450 mayinclude a touchscreen user interface infrastructure 5452. The cloudmanagement subsystem 5460 may include a cloud connectivityinfrastructure 5462. The assay control subsystem 5470 may include acontroller area network (CAN) device control subsystem 5472 and a cameracontrol subsystem 5474. The CAN device control subsystem 5472 mayconnect to other boards controlling other sensors, actuators, heaters,illumination sources, or other components of connected sample handlingapparatuses 400, 1400, and 3000. The camera interface 5414 may beconfigured to control and record images/videos using the image capturedevice(s).

FIG. 55 is a diagram of an example architecture 5500 of the imagemanagement subsystem 5420 shown in FIG. 54 . The image managementsubsystem 5420 can be configured to perform the image registrationprocesses and workflows described herein in accordance with some exampleimplementations. The image management subsystem 5420 can include animage processing pipeline 5505 and visualization tools 5510.

The image processing pipeline 5505 can include one or more analysispipelines configured to process spatial RNA-seq output and brightfieldand fluorescence microscope images in order to detect samples, alignreads, generate feature-spot matrices, perform clustering and geneexpression analysis, and place spots in spatial context on the substrateimage. In some embodiments, the image processing pipeline 5505 caninclude functionality configured to correctly demultiplex sequencingruns and to convert barcode and read data to FASTQ formatted files. TheFASTQ format is a text-based format for storing both a biologicalsequence (usually nucleotide sequence) and its corresponding qualityscores. Both the sequence letter and quality score are each encoded witha single ASCII character for brevity. In some embodiments, the imageprocessing pipeline 5505 can include functionality configured to receivea microscope slide image and FASTQ files and to perform alignment,tissue detection, fiducial detection, and barcode location counting. Theimage processing pipeline 5505 uses the spatial barcodes to generatefeature-spot matrices, determine clusters, and perform gene expressionanalysis. In some embodiments, the image processing pipeline 5505 caninclude functionality configured to receive the output of multiple runsof counting barcode locations and/or unique molecular identifiers (UMI)from related samples and can aggregate the output, normalizing thoseruns to the same sequencing depth, and then recomputing thefeature-barcode matrices and the analysis on the combined data. Theimage processing pipeline 5505 can combine data from multiple samplesinto an experiment-wide feature-barcode matrix and analysis.

The image processing pipeline 5505 can further include functionalityconfigured to process brightfield and fluorescence imaging. For example,the image processing pipeline 5505 can be configured to receive a slideimage as input to be used as an anatomical map on which gene expressionmeasures are visualized. The image processing pipeline 5505 can beconfigured to receive at least two styles of images: a) a brightfieldimage stained with hematoxylin and eosin (H&E) with dark tissue on alight background or b) a fluorescence image with bright signal on a darkbackground. While brightfield input can comprises a single image, thefluorescence input can comprise one or more channels of informationgenerated by separate excitations of the sample.

The image processing pipeline 5505 can further include functionality toautomatically and/or manually perform image processing workflowsdescribed herein. For example, the image processing pipeline 5505 caninclude functionality configured to align a substrates barcoded spotpattern to an input substrate image for brightfield images. The imageprocessing pipeline 5505 can further discriminate between tissue andbackground in a slide for brightfield images. The image processingpipeline 5505 can also be configured to prepare full-resolution slideimages for use with the visualization tools 5510.

The image processing pipeline 5505 can be configured with one or moreimaging algorithms. The imaging algorithms can be configured todetermine where a sample, such as tissue, has been placed and aligningthe printed fiducial spot pattern. Tissue detection can be used toidentify which capture spots, and therefore which barcodes, will be usedfor analysis. Fiducial alignment can be performed to determine where inthe image an individual barcoded spot resides, since each user may set aslightly different field of view when imaging the sample area. The imageprocessing analysis pipeline 5505 can also be configured to supportmanual alignment and tissue selection via the visualization tools 5510.

The image processing pipeline 5505 can perform fiducial alignment byidentifying the slide-specific pattern of invisible capture spotsprinted on each slide and how these relate to the visible fiducial spotsthat form a frame around each capture area. The fiducial frame caninclude unique corners and sides that the software attempts to identify.To determine alignment of fiducials, the image processing pipeline 5505can extracts features that “look” like fiducial spots and then canattempt to align these candidate fiducial spots to the known fiducialspot pattern. The spots extracted from the image can necessarily containsome misses, for instance in places where the fiducial spots werecovered by tissue, and some false positives, such as where debris on theslide or tissue features may look like fiducial spots.

After extraction of putative fiducial spots from the image, this patterncan be aligned to the known fiducial spot pattern in a manner that isrobust to a reasonable number of false positives and false negatives.The output of this process can be a coordinate transform that relatesthe barcoded spot pattern to the user's tissue image. In someembodiments, the fiducial alignment algorithm can be executed for eachof the possible fiducial frame transformations and choosing among thosethe alignment with the best fit.

The image processing pipeline 5505 can further include tissue detectionfunctionality. Each area in a substrate or slide can contain a grid ofcapture spots populated with spatially barcoded probes for capturingpoly-adenylated mRNA. Only a fraction of these spots can be covered bytissue. In order to restrict the image processing pipeline 5505 analysisto only those spots where tissue was placed, the image processingpipeline 5505 can use an algorithm to identify tissue in the inputbrightfield image. For example, using a grayscale, down-sampled versionof an input image, multiple estimates of tissue section placement can becalculated and compared. These estimates can be used to train astatistical classifier to label each pixel within the capture area aseither tissue or background. In order to achieve optimal results, thetissue detection algorithm can be configured to receive an image with asmooth, bright background and darker tissue with a complex structure.

As further shown in FIG. 55 , the image management subsystem 5420 canalso include visualization tools 5510. The visualization tools 5510 canbe configured to provide the spatialomic (e.g., spatial transcriptomic)data in one or more visual formats. The visualization tools 5510 canprovide the spatialomic (e.g., spatial transcriptomic) data for displayin a display of the sample handling apparatus 400, 1400, and 3000. Insome embodiments, the spatialomic (e.g., spatial transcriptomic) datacan be provided in a GUI of the display of the sample handling apparatus400, 1400, and 3000. In some embodiments, the visualization tools 5510can be configured on a remote computing device that is communicativelycoupled to the sample handling apparatus 400, 1400, and 3000, such thatthe spatialomic (e.g., spatial transcriptomic) data can be visualizedand/or manipulated on the remote computing device.

The visualization tools 5510 can be configured to provide a user inputsystem and user interface, such as a desktop application that providesinteractive visualization functionality to analyze data from differentspatialomic (e.g., spatial transcriptomic) processes and workflowsdescribed herein. The visualization tools 5510 can include a browserthat can be configured to enable users to evaluate and interact withdifferent views of the spatialomic (e.g., spatial transcriptomic) datato quickly gain insights into the underlying biology of the samplesbeing analyzed. The browser can be configured to evaluate significantgenes, characterize and refine clusters of data, and to performdifferential expression analysis within the spatial context of a sampleimage.

The visualization tools 5510 can be configured to read from and write tofiles generated by the image processing pipeline 5505. The files can beconfigured to include tiled and untiled versions of sample images, geneexpression data for all barcoded locations on a substrate or slide,alignment data associated with alignment of a sample or portions of thesample and the barcoded locations of an array, and gene expression-basedclustering information for the barcoded locations. The geneexpression-based clustering information can include t-DistributedStochastic Neighbor Embedding (t-SNE) and Uniform Manifold Approximationand Projection (UMAP) projections.

FIG. 56 is a diagram illustrating an example architecture of a computingsystem 5605. The computing system 5605 can include a first computingdevice 5610 and a second computing device 5630. In some embodiments, thecomputing device 5610 can be the same as computing device 5360 describedin relation to FIG. 53 . In some embodiments, the computing device 5610can be communicatively coupled with the computing device 5630, forexample when the computing device 5630 is configured as or withininstrument 400, 1400, and 3000 described herein.

As shown in FIG. 56 , the computing device 5610 includes at least oneprocessor 5640 for performing actions in accordance with instructions,and one or more memory devices (e.g., cache 5645) and/or memory 5650 forstoring instructions and data. The computing device 5610 includes one ormore processors 5640 in communication, via a bus 5615, with memory 5650and with at least one network interface controller 5620 with a networkinterface 5625 for connecting to external devices, such as computingdevice 5630, e.g., a computing device (such as the instrument 400, 1400,3000 herein). The one or more processors 5640 are also in communication,via the bus 5615, with each other and with any I/O devices at one ormore I/O interfaces 5625, and any other devices 5660. The processor 5640illustrated can be incorporated, or can be directly connected to, cachememory 5645. Generally, a processor will execute instructions receivedfrom memory.

The network interface controller 5620 manages data exchanges via thenetwork interface 5625. The network interface controller 5620 handlesthe physical and data link layers of the Open Systems Interconnect (OSI)model for network communication. In some implementations, some of thenetwork interface controller's tasks are handled by the processor 5640.In some implementations, the network interface controller 5620 is partof the processor 5640. In some implementations, the computing device5610 has multiple network interface controllers 5620. In someimplementations, the network interface 5625 is a connection point for aphysical network link, e.g., an RJ 45 connector. In someimplementations, the network interface controller 5620 supports wirelessnetwork connections and an interface port 5625 is a wirelessreceiver/transmitter. Generally, the computing device 5610 can exchangedata with other network devices 5630, such as the sampling handlingapparatus 400, 1400, and 3000 described herein via physical or wirelesslinks to a network interface 5625. In some implementations, the networkinterface controller 5620 implements a network protocol, such asEthernet.

The other computing devices 5630 are connected to the computing device5610 via a network interface port 5625. The other computing device 5630can be a peer computing device, a network device, or any other computingdevice with network functionality. In some embodiments, the computingdevice 5630 can be a network device such as a hub, a bridge, a switch,or a router, connecting the computing device 5360 to a data network suchas the Internet. In some embodiments, the computing device 5610 can becommunicatively coupled to the computing device 5630 (e.g., theinstrument 400, 1400, and 3000) via the I/O interface 5635. In someimplementations an I/O device is incorporated into the computing device5610, e.g., as would be configured on a touch screen computing device ora tablet computing device.

In some uses, the I/O interface 5635 supports an input device and/or anoutput device. In some uses, the input device and the output device areintegrated into the same hardware, e.g., as in a touch screen. In someuses, such as in a server context, there is no I/O interface 5635 or theI/O interface 5635 is not used.

In more detail, the processor 5640 can be any logic circuitry thatprocesses instructions, e.g., instructions fetched from the memory 5650or cache 5645. In many embodiments, the processor 5640 is an embeddedprocessor, a microprocessor unit or special purpose processor. In someembodiments, the functionality described in relation to computing device5610 can be configured on any processor, e.g., suitable digital signalprocessor (DSP), or set of processors, capable of operating as describedherein. In some embodiments, the processor 5640 can be a single core ormulti-core processor. In some embodiments, the processor 5640 can becomposed of multiple processors.

The cache memory 5645 is generally a form of high-speed computer memoryplaced in close proximity to the processor 5640 for fast read/writetimes. In some implementations, the cache memory 5645 is part of, or onthe same chip as, the processor 5640.

The memory 5650 can be any device suitable for storing computer readabledata. The memory 5650 can be a device with fixed storage or a device forreading removable storage media. Examples include all forms ofnon-volatile memory, media and memory devices, semiconductor memorydevices (e.g., EPROM, EEPROM, SDRAM, flash memory devices, and all typesof solid state memory), magnetic disks, and magneto optical disks. Thecomputing device 5610 can have any number of memory devices 5650.

The memory 5650 can include one or more applications 5655. Theapplications 5655 can include programmatic instructions and userinterfaces configured to transmit and receive data corresponding toimage data and/or assay data generated by the sample handling apparatus400, 1400, 3000. In some embodiments, the application 5655 can beconfigured to share data with the operating system 5410, the remoteprocessing service 5355, and/or the support portal 5360.

The applications 5655 can allow a user to receive data regardingexperimental workflows, samples, and settings of the sample handlingapparatus 400, 1400, and 3000. The applications 5655 can includefeatures and functionality for a user to visualize assay progress orresults, or to monitor and control progress of an assay. In this way,the applications 5655 can provide monitoring such that in-person,on-site monitoring may not be required for some or all of an assayworkflow. In some embodiments, the applications 5655 can includefeatures or functionality to order consumables, such as reagents orstains, used in conjunction with assays performed using the samplehandling apparatus 400, 1400, 3000.

In some embodiments, the applications 5655 can allow a user to annotatea region of interest on a slide or substrate. For example, theapplications 5655 can provide a display of an image of a tissue sampleon a substrate, an image of an array on a substrate, or an image of atissue sample substrate overlaid with an array substrate in a sandwichconfiguration described herein. A user can interact with theapplications 5655 to provide an input identifying a region of interest.The input can be provided with a mouse, a stylus, a touch-screen or thelike. The input can be processed by the application 5655 and displayedon an image of the sample substrate, the array substrate, or the tissuesample substrate overlaid with an array substrate. In some embodiments,the sample handling apparatus 400, 1400, and 3000 can receive dataassociated with the user input annotation and can apply the annotate tothe sample substrate, the array substrate, or the tissue samplesubstrate overlaid with an array substrate.

In some embodiments, the applications 5655 can provide features andfunctionality for a user to review assay results or image data, evaluateassay results or image data using additional processing techniques orcomponents, as well as commenting on and sharing assay results and imagedata. The applications 5655 can also enable a user to report issues andtrack the status of issued about the operation of the sample handlingapparatus 400, 1400, and 3000 to the support portal 5360. As such, theuser's customer support experience can be elevated as the applicationscan enable direct access to an error without requiring the user toseparately write lengthy emails and collect log files or operatingparameters of the sample handling apparatus 400, 1400, 3000 to provideto the customer support team. In some embodiments, the applications 5360can provide documentation, such as training materials, assay or reagentdata, and user manuals for the sample handling apparatus 400, 1400, and3000. For example, the applications 5655 can immediately inform the userof updated user guides and product improvements. In some embodiments,the applications 5655 can provide a user with easy access to tutorialsand interactive instruction.

A user interacting with applications 5655 on computing device 5610, sucha mobile phone, tablet, or personal computing device, can providefeedback about the sample handling apparatus 400, 1400, and 3000 to acustomer support team, for example via the support portal 5360. Thecustomer support team can interact back with the user to provide timely,actionable insights about the state and operations of the samplehandling apparatus 400, 1400, and 3000 to improve the user's experienceand the likelihood of more successful experimental outcomes. In thisway, the customer support team can reduce diagnostic time and solutionimplementation time. In some embodiments, the applications 5655 can beconfigured to receive and install software updates or patches associatedwith the operating system 5410 or the applications 5655. In this way,the applications 5655 can help automatically or manually configure andinitialize the sampling handling apparatus 400, 1400, and 3000. Forexample, the customer support team may access the sample handlingapparatus via the applications 5655 and can directly access an erroronce notified of the issue by an application 5655. Thus, in someembodiments, the applications 5655 can generate alerts and notificationsassociated assays and configurations of the sample handling apparatus400, 1400, and 3000. For example, in a customer support context, when aprotocol or experimental workflow is determined or an addition to anassay is made, the applications 5655 can notify the user. Theapplications 5655 can instantiate the update on the sample handlingapparatus 400, 1400, and 3000 such that the user can access the updatesprotocol immediately.

In some embodiments, other devices 5660 are in communication with thecomputing devices 5610 or 5630. In some embodiments, the other devices5660 can include external computing or data storage devices connectedvia a universal serial bus (USB). The other devices 5660 can alsoinclude an I/O interface, communication ports and interfaces, and dataprocessors. For example, the other devices can include a keyboard,microphone, mouse, or other pointing devices, output devices such as avideo display, a speaker, or a printer. In some embodiments, the otherdevices 5660 can include additional memory devices (e.g., portable flashdrive or external media drive). In some implementations, the otherdevices can include a co-processor. In some embodiments, the additionaldevice 5660 can include an FPGA, an ASIC, or a GPU to assist theprocessor 5640 with high precision or complex calculations associatedwith the image processing and image registration methods describedherein.

FIG. 57 is an example interface display 5700 provided by thevisualization tools 5410 described herein in accordance with someexample implementations. The interface display 5700 can include imagesetting functionality 5705 configured to adjust or configured settingsassociated with fiducial display, scale display, rotation, and resettingthe image data. The interface display 5700 can also include one or moreimage manipulation tools 5710, such as a pointer to select data or menuitems, a lasso to select data, and a pen to annotate or mark data or aregion of interest on a slide or an image of slide(s). The spatialomic(e.g., spatial transcriptomic) data can be provided in a primary viewingpanel 5715.

As shown in FIG. 57 , the interface display 5700 can include apresentation 5720 of gene/feature expression data organized with respectto clusters. In some embodiments, the presentation 5720 can providerepresentative clusters as violin plots, although a number of othernon-limiting plot types can be envisioned. The interface display 5700can also include secondary viewing panels 5725 and 5730. The secondaryviewing panels 5725 and 5730 can provide one or more projections of thespatialomic (e.g., spatial transcriptomic) data provided in the primaryviewing panel 5715. For example, the secondary viewing panel 5725 canprovide a spatial projection of the spatialomic (e.g., spatialtranscriptomic) data so that a user can interact with the spatialopacity and magnification settings of the data. The secondary viewingpanel 5730 can provide an additional projection of the spatialomic(e.g., spatial transcriptomic) data, such as a t-SNE projection shown inFIG. 57 . The primary viewing panel 5715 and secondary viewing panels5725 and 5730 can each individually be configured with imagemanipulation tools 5510 including, but not limited to, image resizefunctionality, image cropping functionality, image zoom functionality,image capture functionality, tile view functionality, list viewfunctionality, or the like.

VI. Fiducial Detection Using Image Registration System

For spatialomic (e.g., spatial transcriptomic) applications performedusing the systems, methods, and computer readable mediums describedherein, analyte information can be displayed over high resolution tissueimages. An array of barcoded spots can capture analytes from a sample(e.g. a sample of a tissue section) for downstream sequencing. Thelocation of the spots on an array substrate or slide relative to thelocation of the sample on a sample slide or substrate can be inferredusing fiducial markers that can placed on the array substrate that canbe imaged along with the tissue section on the sample substrate. Thesample handling apparatuses, such as the sample handling apparatuses400, 1400, or 3000 described herein can enable spatialomic (e.g.,spatial transcriptomic) assays without having to first place a sample ofa tissue selection directly on the array substrate that includes thearray of barcoded spots. The sample handling apparatuses 400, 1400, or3000 described herein can be configured to form an overlay or sandwichof a sample substrate and an array substrate. The overlay or sandwichcan be formed and assembled during a permeabilization step in which apermeabilization solution can be introduced into the overlay or sandwichof the sample substrate and the array substrate. Duringpermeabilization, the sample can be permeabilized or digested and canrelease transcripts that can diffuse across a gap formed between thesample substrate and the array substrate (e.g., from the tissue sampleto the array of barcoded spots) and can bind on the barcoded oligospresent within the barcoded spots. Because this transcript release andcapture is done in the confined overlay or sandwich configuration of thesample substrate and the array substrate, it can be challenging toexchange reagents during this step to ensure sufficient fluid dispersaland control of reagent distribution so that spatial visualization oftranscripts can be achieved under optimal conditions. When the sampleoverlaps the fiducials it can be difficult to visualize the fiducialsfor robust detection and subsequent image processing. This can affectthe alignment of array images to sample images necessary to perform thespatialomic (e.g., spatial transcriptomic) workflows described herein.

FIGS. 58A-58B depict a configuration of a sample and an array in whicharray fiducials are not overlapped with the sample in acquired imagedata in accordance with some example implementations. As shown in FIG.58A, the sample handling apparatuses 400, 1400, or 3000 can acquireimage data of a sample substrate 5805 including a sample 5810 thereonoverlaid with an array substrate 5815. The array substrate 5815 caninclude an array 5820 and an array fiducial 5825. In some embodiments, afiducial frame can include a plurality of individual array fiducials5825 in a patterned arrangement that surrounds the array 5820. The arrayfiducial 5825 can delineate and identify a location of the array 5820 onthe array substrate 5815. Images of the overlay can be acquired viaimage capture device 5830 (corresponding to image capture device 1720described herein). The images and corresponding image data associatedwith the image can be acquired at one or more focal planes,illuminations, and frame rates as will be further described.

As shown in FIG. 58B, an image 5835 of the overlay can be acquired andcan include the sample 5810 and the fiducial 5825. As shown, the sample5810 has been provided such that it does not obscure or overlap thearray fiducial 5825. In this way, the image 5835 includes both thesample 5810 and the array fiducial 5825 in the image. As the position ofthe array fiducial 5825 is known relative to the array 5820 of barcodedspots and the barcoded spots are not visible in the image 5835 of theoverlay, the position of the array fiducial 5825 can be used todetermine the location or position of the barcoded spots of the array5820 relative to the location or position of the sample 5810.

In conditions in which the sample 5810 is not covering the arrayfiducial 5825, as shown in image 5835, the location of the arrayfiducials 5825 relative to the location of the sample 5810 can bedetermined using the sample handling apparatus 400, 1400, or 3000 byfirst loading the sample substrate and the array substrate into thesample handling apparatus and bringing the sample substrate 5805 inproximity of the array substrate 5815 to form the overlay or sandwich ofthe sample 5810 and the array 5820. Image data can be acquired via theimage capture device 5830 of the overlay including the sample 5810, thearray 5820, and the array fiducials 5825 as shown in image 5835. Acomputing device communicably coupled to the image capture device 5830and the sample handling apparatus 400, 1400, or 3000 can receive imagedata including the image 5835 and can detect the location of the arrayfiducials 5825 with respect to a coordinate system determined andapplied to the image data by the computing device. The computing devicecan further detect the location of the sample 5810 in the image 5835using the coordinate system. Since the location of the sample 5810 andlocation of the array fiducials 5825 are determined by the computingdevice in the same image 5835 and using the same coordinate system, thelocation of the array fiducials 5825 relative to the location of thesample 5810 can be determined and provided by the computing device.However, in some conditions, the sample 5810 can overlap and obscure thearray fiducials 5825 making it difficult to determine the location ofthe location of the array fiducials 5825 relative to the location of thesample 5810. The systems, methods, and computer readable mediumsdescribed herein provide improved detection of array fiducials.

FIG. 59 is a process flow diagram illustrating an example process 5900for detecting fiducials associated with an array in accordance with someexample implementations. The process 5900 can be performed by the system5300 configured with the software architecture 5400 and the examplearchitecture 5500 of the image management subsystem 5420.

For example, in operation 5910 the processor 5320 can receive image dataacquired via an image capture device, such as image capture device 1720.The image data can include an image of an array and an array fiducialoverlaid atop a sample.

In operation, 5920, the processor 5320 can receive image data, acquiredvia the image capture device 1720, including an image of an overlay ofthe array with the sample as described in relation to FIGS. 58A-58Bafter the sample substrate 5805 has been overlaid or sandwiched withrespect to the array substrate 5815. The sample handling apparatus 400,1400, and 3000 can prevent movement of the slide substrate relative tothe array substrate as the overlay or sandwich is formed using thesample handling apparatus. The sample handling apparatus 400, 1400, and3000 can also prevent movement of the array substrate relative to theimage capture device 1720. The image of the overlay can also include thearray fiducial. The sample can be located relative to the array suchthat the sample obscures the array fiducial in the overlay. The samplemay not fully obscure the array fiducial, but instead may obscure aportion of the array fiducial so as to limit or reduce the improvedarray fiducial detection described herein.

In operation 5930, the processor 5320 can determine the location of thearray fiducial based on the image data and the image including the arrayand the array fiducial. The processor 5320 can determine the location ofthe array fiducial based on a coordinate system. In some embodiments,image data includes the coordinate system, wherein pixel data is storedin the coordinate system. In some embodiments, the image data comprisesdata of pixel values stored in the coordinate system. In someembodiments, the image data comprises data of pixel values that arestored in a matrix coordinate system. In some embodiments, thecoordinate system is stored within the memory 5320 or otherwiseaccessible to the operating system 5410 (such as the image managementsubsystem 5420, or the I/O control board 5305). In some embodiments, thememory 5320 or operating system 5410 can store or access one or moreunique and different coordinate systems. In some embodiments, thecoordinate systems can include one-, two-, or three-dimensionalcartesian coordinate systems. The processor 5320 can apply thecoordinate system coordinates to one or more features of the receivedimage data so that locations of features in the image data, such asarray fiducial locations and/or sample locations can be known withrespect to the coordinate system coordinates.

In operation 5940, the processor 5320 can determine a location of thesample based on the image data and the image including the overlay ofthe array with the sample and further including the array fiducial. Thearray fiducials may be obscured in this image data by the sample and maynot be visible. The location of the sample can be determined in thecoordinate system by the data processor 5320 in a similar manner asdescribed in relation to determining the location of the array fiducialin operation 5930.

In operation 5950, the data processor 5320 can compare the location ofthe array fiducial determined in operation 5930 and the location of thesample determined in operation 5940. Since there is no presumed shift inthe sample substrate and the array substrate relative to each other orto one or more image capture device(s) 1720 between the capture of thefirst and second images, the locations can be considered within the samecoordinate system and the processor 5320 can perform the comparison toconfirm such. In operation 5960, based on the comparing, the processor5320 can provide the location of the array fiducials relative to thelocation of the sample as defined by the coordinate system in which eachhave been determined to be located within. In some embodiments, theprocessor 5320 can provide the location of the array fiducial and thelocation of the sample in the display 5335 and/or the graphical userinterface 5340.

FIGS. 60A-60B depict a workflow 6000 for detecting array fiducialsoverlapped with a sample in acquired image data in accordance with someexample implementations. The workflow 6000 can be performed with respectto embodiments of process 5900 described in FIG. 59 . As shown in FIG.60A, the image capture device 6020 (corresponding to image capturedevice 1720) can acquire an image 6025. The image 6025 can be of anarray substrate 6005, which can include an array fiducial 6010 and anarray 6015. The image 6025 can include the array substrate 6005 and thearray fiducial 6010. As shown in FIG. 60B, an overlay 6055 of the samplesubstrate 6040 including a sample 6045 can be formed in the samplehandling apparatus 400, 1400, or 3000 with the array substrate 6005. Theimage capture device 6020 can acquire an image 6050 of the overlay 6055.The image 6050 can include the array fiducial 6010 overlapped andobscured by the sample 6045.

FIGS. 61A-61B depict a workflow 6100 for detecting array fiducialsoverlapped with a sample in image data acquired at different focalplanes in accordance with some example implementations. The workflow6100 can be performed with respect to embodiments of process 5900 ofFIG. 59 . The sample handling apparatus 400, 1400, and 3000 can beconfigured to move the image capture device 6135 in a vertical directionwith respect to the z-axis, while remaining fixed in the x-, y-axesrelative to the array substrate 6115.

As shown in FIG. 61A, image data can be acquired of an overlay 6125 ofthe sample substrate 6105 and the array substrate 6115. The samplesubstrate 6105 can include the sample 6110 and the array substrate caninclude the array fiducials 6120. The image data can be acquired by theimage capture device 6135 (corresponding to image capture device 1720)at a focal plane 6130. The focal plane can correspond to a focal depthat which image data associated with the overlay 6125 is acquired. In thefocal plane 6130 shown in FIG. 61A, the overlay 6125 may not becompletely captured, for example the sample substrate 6105 and thesample 6110 may be out of focus, while the array substrate 6115 and thearray fiducials 6120 can be more visible. The image 6140 captured by theimage capture device 6135 of the overlay 6125 can reflect thissuboptimal focal depth such that the array fiducials 6120 can be shownin the image 6140 in greater focus, while the sample 6110 is shown outof focus.

In FIG. 61B, the focal plane captures the overlay 6125 of the sample6110 and the array fiducials 6120 more optimally. The image 6150captured by image capture device 6135 can include the overlay 6125 andspecifically, the sample 6110 and the array fiducials 6120, in focus.Image 6140 can be used detection of the array fiducials directly, or toaid detection of the array fiducials using image 6150. As there was isno presumed shift in the overlay 6125 relative to the image capturedevice 6135 in the x- and y-axes during formation of the overlay bysandwiching the sample substrate 6105 and the array substrate 6115, bothsubstrates are present in the same coordinate system.

FIGS. 62A-62B depict a workflow 6200 for detecting array fiducialsoverlapped with a sample in image data acquired at differentilluminations in accordance with some example implementations. Theworkflow 6200 can be performed with respect to embodiments of process5900 described in relation to FIG. 59 . The sample handling apparatus400, 1400, and 3000 can be configured with a light source 6240configured to provide light at one or more illumination setting duringthe image acquisition steps described in relation to the process 5900.Although the light source 6240 is shown oriented above the overlay 6225,a variety of non-limiting numbers, configurations, and orientations ofthe light source 6240 can be included in the sample handling apparatus400, 1400, and 3000. For example, in some embodiments, the light source6240 can be configured below the overlay 6225. The light source can emitcolored RGB light in various wavelengths. In some embodiments, the lightsource and illumination settings can be associated with one or morewavelengths that are close to or match the absorbance wavelength of oneor more dyes used to stain the sample, such as an eosin dye or afluorescent dye. In some embodiments, the light source and illuminationsettings can be configured to improve array fiducial contrast and/orsample contrast. In some embodiments, the processor 5320 can selectimage data or filter the image data associated with one or more RGBchannels of the light source 6240.

As shown in FIG. 62A, the light source 6240 can provide an illumination6230 on to the overlay 6225. The illumination 6230 can correspond to awavelength configured to improve a contrast of the array fiducials 6220.For example, an illumination between 550 nm and 1 μm can maximizecontrast of the array fiducial relative to the contrast of an Eosinstained sample since the absorption band associated with the Eosin stainis 440 nm to ˜550 nm. When the image 6245 is captured, the contrast ofthe array fiducial 6220 is improved with respect to the sample 6210 asshown in the image 6245 of the overlay 6225. For example, theillumination 6230 can include a red or an infrared (IR) illumination. Asshown in FIG. 61B, the light source 6240 can provide an illumination6250 on to the overlay 6225. The illumination 6250 can correspond to awavelength configured to improve a contrast of the sample 6210 as shownin image 6255 of the overlay 6225. For example, the illumination 6250can include a green illumination. In some embodiments, the illuminations6230 and 6250 can include wavelengths between 500 nm and 1 mm. In someembodiments, the illuminations can include wavelengths between 500 nmand 530 nm, between 525 nm and 550 nm, between 540 and 570 nm, between560 and 585 nm, between 580 nm and 700 nm, between 600 nm and 800 nm,between 700 nm and 1 mm, and between 850 nm and 1 μm. Image 6245 can beused directly for detection of the array fiducials 6220 or to aiddetection of the array fiducials 6220 in image 6255. If there is nopresumed shift in the sample substrate and the array substrate relativeto each other or to one or more image capture device(s) 6235 between thecapture of images at the different illuminations, the locations can beconsidered within the same coordinate system and the processor 5320 canperform the comparison to confirm such.

FIGS. 63A-63B are images illustrating image data acquired at differentilluminations in accordance with some example implementations. As shownin FIG. 63A, an IR illumination can maximize contrast of the arrayfiducials 6305. As shown in FIG. 63B, a green illumination can maximizecontrast of the sample of a tissue 6310.

FIG. 64 is a process flow diagram illustrating an example process 6400for detecting fiducials associated with an array using instrumentfiducials provided in a sample handling apparatus in accordance withsome example implementations. The process 6400 can be performed withrespect to embodiments described in relation to process 5900 of FIG. 59. The sample handling apparatus can include one or more instrumentfiducials as described in relation to FIG. 41 . The instrument fiducialscan provide high contrast marks that are easily visible through samplesof tissue. The array image data of the array image acquired in operation5910 can further include an instrument fiducial configured on the samplehandling apparatus. In this way, the location of the instrumentfiducials relative to the array fiducials can be determined.

In operation 6410, the processor 5320 can receive array image data, suchas in operation 5920, including an instrument fiducial in the image withthe overlay of the sample, the array, and the array fiducial. The samplecan obscure the array fiducial and the instrument fiducial in theoverlay. In this way, the location of the instrument fiducials to thesample location can be determined. The array fiducials may not be easilyvisible if they are covered by the sample.

In operation 6420, the processor 5320 can determine the location of thearray fiducial relative to the instrument fiducial in the array imagedata captured in operation 5910 and now including the instrumentfiducial based on the coordinate system used in operation 5910.

In operation 6430, the processor 5320 can determine the location of thesample relative to the instrument fiducial captured in the array imagedata acquired in operation 5910. The location of the sample relative tothe instrument fiducial can be determined using the array image dataacquired in operation 6410. The location of the sample relative to theinstrument fiducial can be determined using a second, or alternatecoordinate system that is different than the coordinate system used todetermine the location of the array fiducials relative to the instrumentfiducials in operation 6420.

In operation 6440, the processor 5320 can compare the location of thearray fiducial in the array image acquired in operation 5910 and furtherincluding the instrument fiducial with the location of the sample in thearray image acquired in operation 6410. Since the location of the arrayfiducials are known relative to the location of the sample, and thelocation of the instrument fiducials are known relative to the locationof the array fiducial, the location of the sample to the array fiducialcan be determined based on the differences between the locations in thetwo coordinate systems.

FIGS. 65A-65B depict a workflow 6500 for detecting array fiducialsoverlapped with a sample in image data including instrument fiducialsprovided in a sample handling apparatus in accordance with some exampleimplementations. The workflow 6500 can be performed with respect toembodiments described in relation to process 5900 of FIG. 59 . As shownin FIG. 65A, an array substrate 6505 including an array fiducial 6510can be positioned in or on a holding member 6515 (corresponding tomember 410). The holding member 6515 can include one more instrumentfiducials 6520. Image capture device 6525 can acquire image 6530including image data of the array fiducial 6510 and the instrumentfiducial 6520. As shown in FIG. 65B, the image capture device 6525 canfurther acquire image data including image 6550 of the overlay 6535including the sample 6545 overlaid with the array fiducial 6510 and theinstrument fiducial 6520. The array fiducials 6510 can be obscured orcovered by the sample 6545, however the location of the array fiducials6510 can be determined using the instrument fiducials 6520 due to thehigh contrast and visibility of the instrument fiducials 6520 relativeto the sample 6545.

FIG. 66 is a process flow diagram illustrating an example process 6600for detecting fiducials applied to a substrate on which an array islocated in accordance with some example implementations. The process6600 can be performed with respect to embodiments described in relationto process 5900 of FIG. 59 .

In some embodiments, applied fiducials can include a stamp, a sticker, aspacer, a drawing, printed spots, or a laser etching applied to andlocated on a substrate on which the array and the array fiducial can belocated. Spacers can be applied to an array substrate to provide flowcontrol of a permeabilization reagent used during the permeabilizationprocesses described herein. The spacers can provide an amount ofseparation between an array substrate and a sample substrate such thatwhen the array substrate and sample substrate are brought into contact,the spacer can function to maintain the amount of separation between thetwo substrates. The spacers can include high contrast materials that canbe visible when covered or obscured by a sample of tissue. For example,in some embodiments, the spacers can include a graphite material formedfrom a graphite sheet. Graphite is a dark material and can provide ahigh contrast spacer without requiring additional high contrast finishesbe applied to the spacer. In some embodiments, the spacers can include ahigh contrast finish applied to a spacer material. For example, a darkblack finish can be applied to a transparent polyester material tocreate a high contrast spacer. The spacers can be fixed to the arraysubstrate to prevent movement relative to the array substrate during theformation of the overlay formed by closing the substrate holding member404 onto the substrate holding member 410. In some embodiments, thespacers can be opaque.

In some embodiments, applied fiducials can be formed from a materialincluding a dye, a chemical, a contrast agent, or a nanoparticle. Theapplied fiducials can be configured to improve the contrast of thefiducial when obscured by a sample of tissue during imaging so that theyare more readily visible to the human eye or to an image capture devicewhen illuminated at specific wavelengths. For example, goldnanoparticles of different sizes and shapes can be used to providedifferent contrasts at different wavelengths. The array image data ofthe array image acquired in operation 5910 can further include anapplied fiducial applied to the substrate on which the array and arrayfiducial are located. In this way, the location of the applied fiducialsrelative to the array fiducials can be determined.

In operation 6610, the processor 5320 can receive image data, such as inoperation 5920, that further includes an applied fiducial that has beenapplied to the substrate on which the array and array fiducial arelocated. In this way, the location of the applied fiducials relative tothe array fiducials can be determined. The array fiducials may not beeasily visible if they are covered by the sample.

In operation 6620, the processor 5320 can determine the location of thearray fiducial relative to the applied fiducial in the array image datacaptured in operation 5910 and now including the applied fiducial basedon the coordinate system used in operation 5910.

In operation 6630, the processor 5320 can determine the location of thesample relative to the applied fiducial captured in the array image dataacquired in operation 5910. The location of the sample relative to theapplied fiducial can be determined using the array image data acquiredin operation 6610. The location of the sample relative to the appliedfiducial can be determined using a second, or alternate coordinatesystem that is different than the coordinate system used to determinethe location of the array fiducials relative to the applied fiducials inoperation 6620.

In operation 6640, the processor 5320 can compare the location of thearray fiducial in the array image acquired in operation 5910 and furtherincluding the applied fiducial with the location of the sample in thearray image acquired in operation 6610. Since the location of the arrayfiducials are known relative to the location of the sample, and thelocation of the applied fiducials are known relative to the location ofthe array fiducial, the location of the sample to the array fiducial canbe determined based on the differences between the locations in the twocoordinate systems.

FIGS. 67A-67B depict a workflow 6700 for detecting array fiducialsoverlapped with a sample in image data including fiducials applied to asubstrate on which an array is located in accordance with some exampleimplementations. The workflow 6700 can be performed with respect toembodiments described in process 5900 of FIG. 59 and process 6600 ofFIG. 66 . As shown in FIG. 67A, image capture device 6720 (correspondingto image capture device 1720) can acquire image data including an image6725. The image 6725 can include an array substrate 6705, an arrayfiducial 6710, and an applied fiducial 6715 that has been applied to thearray substrate 6705. The image 6725 can be used to determine theposition of the applied fiducials 6715 relative to the array fiducials6710. In some embodiments, the applied fiducials 6715

As shown in FIG. 67B, image capture device 6720 can acquire image dataof an image data including image 6745. The image 6745 can include anoverlay 6730 of the sample 6740, the array fiducial 6710, and theapplied fiducial 6715. The image 6745 can used to determine the locationof the sample 6740 relative to the array fiducial 6710 since thelocation of the applied fiducial 6715 relative to the location of thesample 6740 is known and the location of the applied fiducial 6716relative to the array fiducial 6710 is also known.

FIGS. 68A-68B depict a workflow 6800 for detecting array fiducialsoverlapped with a sample in image data acquired in relation topermeabilization of the sample in accordance with some exampleimplementations. The workflow 6800 can be performed with respect toembodiments described in process 5900 of FIG. 59 . Permeabilization ofthe sample using the sample handling apparatus described herein can beperformed in accordance with the descriptions provided in relation toFIG. 3 , FIGS. 29A-29C, and FIGS. 31A-31C. As shown in FIG. 68A, theimage capture device 6825 (corresponding to image capture device 1720)can acquire image data of the overlay 6830 prior to the start or nearthe beginning of sample permeabilization when the overlay 6830 has beeninitially formed by closing the substrate holding member 404 onto thesubstrate holding member 410. The image 6835 can include the sample 6810at high contrast obscuring the array fiducials 6820.

As shown in FIG. 68B, the image capture device 6825 can acquire imagedata including image 6845. Image 6845 can be acquired after a period ofpermeabilization of the sample 6810 has occurred in the overlay 6840.The period of permeabilization can cause the sample to be digested,which can result in the array fiducial 6820 becoming more visible atgreater contrast in the image 6845.

FIG. 69 is a process flow diagram illustrating an example process 6900for detecting fiducials using image registration of sample image dataand array image data acquired in a sample handling apparatus includingspacers configured on an array substrate in accordance with some exampleimplementations, such as those described in relation to FIG. 65 . Theprocess 6900 can be performed in relation to embodiments described inprocess 5900 of FIG. 59 , process 6600 of FIG. 66 , and workflow 6600 ofFIGS. 66A-66B. Image registration methods and techniques can beperformed in regard to the descriptions provided herein in Section IV:Image Registration Devices and Methods.

As shown in FIG. 69 , in operation 6910 the processor 5320 can receivearray image data acquired via the image capture device 1720 andincluding an image of the array fiducial as acquired in operation 5910,described in relation to FIG. 59 , and further including at least onespacer. A variety of non-limiting numbers, shapes, and arrangements ofspacers can be included on the array substrate and thus, in the arrayimage data.

In operation 6920, the processor 5320 can perform image registration asdescribed in relation to FIG. 53 to register the image acquired inoperation 5910, described in relation to FIG. 59 , to the image acquiredin operation 6910 by aligning the location of the array fiducial and thelocation of the sample in a common coordinate system including thecoordinate system applied by the processor 5320 to the image acquired inoperation 5910 described in relation to FIG. 59 and the secondcoordinate system applied by the processor 5320 to the image acquired inoperation 6910.

In operation 6930, the processor 5320 can determine the location of thearray fiducial in the image acquired in operation 5910, described inrelation to FIG. 59 , based on the common coordinate system. Inoperation 6940, the processor 5320 can determine the location of thesample in the image acquired in operation 5910, described in relation toFIG. 59 , based on the common coordinate system. In operation 6950, theprocessor 5320 can compare the location of the array fiducial in theimage acquired in operation 5910 and the location of the sample in theimage acquired in operation 6910 using the common coordinate system.Operations 6930-6950 can be performed as described in relation tooperations 5930-5950 corresponding to the description of FIG. 59 ,except as noted otherwise herein.

FIGS. 70A-70B depict a workflow 7000 for detecting array fiducialsoverlapped with a sample in image data acquired and registered using asample handling apparatus including spacers in accordance with someexample implementations. The workflow 7000 can be performed with respectto embodiments described in process 5900 described in relation to FIG.59 and process 6900 described in relation to FIG. 69 . As shown in FIG.70A, the image capture device 7020 (corresponding to image capturedevice 1720) can acquire image data including an image 7025. The image7025 can include the spacer 7015 in addition to the array fiducial 7010.The spacer 7015 can have a high contrast and can be visible when coveredby the sample 7040.

As shown in FIG. 70B, the image capture device 7020 can acquire imagedata including an image 7045 of the overlay 7030. The image 7045 caninclude the spacer 7015 visible through the sample 7040 obscuring thearray fiducials 7010. In this way, the processor 5320 can perform imageregistration between the image 7025 and the image 7045 to determine thelocation of the location of the array fiducial in image 7025 and thelocation of the sample in image 7045 in order to compare the location ofthe array fiducial 7010 and the location of the sample in image 7045 asdescribed in relation to operations 6930-6950.

FIG. 71 is a process flow diagram illustrating an example process 7100for detecting fiducials overlapped with a sample using imageregistration of sample image data and array image data acquired atmultiple illuminations in a sample handling apparatus including spacersin accordance with some example implementations. The process 7100 can beperformed with respect to embodiments described in process 5900described in relation to FIG. 59 , workflow 6200 described in relationto FIGS. 62A-62B, process 6600 described in relation to FIG. 66 , andworkflow 6700 described in relation to FIGS. 67A-67B. The process 7100can be performed to confirm that sample location and fiducial locationsremain unchanged when illumination conditions have changed. Performingimage registration with respect to the spacer locations can help confirmthe sample location and the fiducial location have not changed. Ifspacer positions have changed, image registration can be used todetermine the location of the sample and the location of the fiducial inthe received image data.

As shown in FIG. 71 , in operation 7110 processor 5320 can receive thearray image data acquired at a first illumination and received inoperation 5920. The array image acquired at the first illumination andreceived in operation 5920 can include the sample overlaid atop asubstrate including an array, an array fiducial, and at least a portionof a spacer visible in the array image acquired at the firstillumination. The processor 5320 can further receive additional orsubsequent array image data including an array image acquired at asecond illumination and including the sample overlaid atop the substrateincluding the array, the array fiducial, and the spacer. In someembodiments, the spacers in the first array image and the second arrayimage can be opaque. The spacer can be visible in the array imageacquired at the second illumination due to its contrast properties. Thecomparison of the array image data of array images acquired at the firstand the second illuminations can be used to determine locations of anarray fiducial and a sample using a common coordinate system.

In some embodiments, the first and/or the second illumination can beselected to increase or decrease an amount of contrast between thesample and the array fiducial. For example, a first illumination canenhance the contrast of the sample compared to the contrast of the arrayfiducial. A second illumination can enhance the contrast of the arrayfiducial compared to the contrast of the sample. The illuminations canbe also selected based on the illumination properties or characteristicsdescribed in relation to FIGS. 62A-62B and FIGS. 63A-63B herein.

In operation 7120, the processor 5320 can determine the location of thearray fiducial in the array image acquired at the first illumination andreceived in operation 5920 and including the spacer visible in the arrayimage acquired at the first illumination. The location of the arrayfiducial can be determined in the array image acquired at the firstillumination based on a first coordinate system. In operation 7130, theprocessor can determine the location of the sample in the array imageacquired at the second illumination and received in operation 7110 basedon a second coordinate system. In some embodiments where there was noshift in the sample substrate, the spacer (or portion thereof) and thearray substrate relative to each other or to one or more image capturedevice(s) between image capture at the first and second illuminations,the second coordinate system can be the same as the first coordinatesystem, e.g., can be a common coordinate system. In other words, thelocations can be considered within the same coordinate system and theprocessor 5320 can perform the comparison to confirm such.

In some embodiments where a shift occurred in, e.g., the spacer orportion thereof relative to the image capture device(s) between imagecapture at the first and second illuminations, image registration may beperformed to transform the second coordinate system to the firstcoordinate system. Alternatively, in some embodiments where a shiftoccurred in, e.g., the spacer or portion thereof relative to the imagecapture device(s) between image capture at the first and secondilluminations, image registration may be performed to transform thefirst coordinate system to the second coordinate system. Alternatively,in some embodiments where a shift occurred in, e.g., the spacer orportion thereof relative to the image capture device(s) between imagecapture at the first and second illuminations, image registration may beperformed to transform the first and second coordinate systems to acommon coordinate system.

In operation 7140, the processor 5320 can register the array imageacquired at the first illumination in operation 5920 including thespacer to the array image acquired at the second illumination andreceived in operation 7110 by aligning the location of the arrayfiducial and the location of the sample in the common coordinate system.The common coordinate system can include the first coordinate system andthe second coordinate system and can also include the location of thearray fiducial and the location of the sample. Alignment methods andtechniques can be performed in regard to the descriptions providedherein in Section III: Sample and Array Alignment Devices and Methods.Image registration methods and techniques can be performed in regard tothe descriptions provided herein in Section IV: Image RegistrationDevices and Methods.

In some embodiments, such as when there was no shift in the samplesubstrate, the spacer (or portion thereof) and the array substraterelative to each other or to one or more image capture device(s) betweenimage capture at the first and second illuminations, and the secondcoordinate system can be the same as the first coordinate system, e.g.,can be a common coordinate system, the operation 7140 can be optionallyomitted as no image registration is needed. In other words, the firstcoordinate system and the second coordinate system can be considered asthe same coordinate system because there is no change in the location ofthe array fiducial and/or the sample.

In operation 7150, the processor 5320 can determine the location of thearray fiducial in the array image acquired at the first illumination andreceived in operation 5920 including the spacer based on the commoncoordinate system. In operation 7160, the processor 5320 can determinethe location of the sample in the array image acquired at the secondillumination and received in operation 7110 based on the commoncoordinate system. In operation 7170, the processor 5320 can compare thelocation of the array fiducial in the array image acquired at the firstillumination and received in operation 5920 including the spacer and thelocation of the sample in the array image acquired at the secondillumination and received in operation 7110 using the common coordinatesystem. In this way, the location of the array fiducials relative to thelocation of the sample can be provided.

In some embodiments, the operations of process 6900 described inrelation to FIG. 69 and the operations of process 7100 described inrelation to FIG. 71 can be combined.

FIGS. 72A-72B depict a workflow 7200 for detecting array fiducialsoverlapped with a sample in image data acquired and registered atmultiple illuminations using a sample handling apparatus includingspacers in accordance with some example implementations. The workflow7200 can be performed with respect to embodiments of process 5900described in relation to FIG. 59 , embodiments of workflow 6200described in relation to FIG. 62 , and embodiments of process 7100described in relation to FIG. 71 .

As shown in FIG. 72A, the image capture device 7235 (corresponding toimage capture device 1720) can acquire image data including image 7250.Image 7250 can include an overlay 7230 of the sample 7210, the arrayfiducial 7220, and the spacer 7225. The image 7250 can be illuminated bylight source 7240 providing an illumination 7245. For example,illumination 7245 can include a red or an infrared (IR) wavelength tomaximize the contrast of the array fiducials 7220. For example, anillumination between 550 nm and 1 μm can maximize contrast of the arrayfiducial relative to the contrast of an Eosin stained sample since theabsorption band associated with the Eosin stain is 440 nm to ˜550 nm.The high contrast spacer 7220 can also be visible in the image 7250.

As shown in FIG. 72B, the image capture device can acquire image dataincluding image 7265. Image 7265 can include an overlay of the sample7210, the array fiducial 7220, and the spacer 7225. The image 7265 canbe illuminated by light source 7240 providing illumination 7260. Forexample, illumination 7260 can include a green wavelength to maximizecontrast of the sample 7210. In some embodiments, more than one lightsource 7240 can be configured in the sample handling apparatus 400,1400, and 3000. In the image 7265, the spacer 7225 and the sample 7210are visible, while the array fiducials 7220 are not visible when coveredby the sample 7210. In some embodiments, the illuminations 7245 and 7260can include wavelengths between 500 nm and 1 mm. In some embodiments,the illuminations can include wavelengths between 500 nm and 530 nm,between 525 nm and 550 nm, between 540 and 570 nm, between 560 and 585nm, between 580 nm and 700 nm, between 600 nm and 800 nm, between 700 nmand 1 mm, and between 850 nm and 1 μm.

FIGS. 73A-73C are images illustrating embodiments of image data acquiredat different illuminations by the sample handling apparatus 400, 1400,and 300 for use in image registration processes and techniques describedin relation to embodiments described in FIGS. 62A-62B and FIGS. 72A-72Bin accordance with some example implementations. As shown in FIG. 73A,an image can be acquired including an array fiducial 7305. In FIG. 73B,an image can be acquired at a green illumination to maximize a contrastbetween the sample 7310 and the array fiducial 7305. In FIG. 73C, animage can be acquired at a red or infrared (IR) illumination to maximizea contrast of the array fiducials 7305.

FIGS. 74A-74B are images illustrating additional embodiments of imagedata acquired at different illuminations by the sample handlingapparatus 400, 1400, and 300 for use in image registration processes andtechniques described in relation to embodiments described in FIGS.62A-62B and FIGS. 72A-72B in accordance with some exampleimplementations. As shown in FIG. 74A, array fiducials can be detectedin an image where the array fiducials 7405 are visible within the image.In FIG. 74B, image registration can be performed on image data includingimages that contain a spacer. In FIG. 74C, a frame of array fiducials7405 can be superimposed over a sample 7410.

In some embodiments, detected array fiducial locations in acquired imagedata can be registered with locations of array fiducials identified in adata file, such as a .gpr file. Based on the image registration, aregistration error can be assigned for each array fiducial. In someembodiments, detected array fiducial locations in acquired lowresolution image data can be registered with detected array fiduciallocations in acquired high resolutions image data. Based on the imageregistration, a registration error can be assigned for each arrayfiducial. Monochromatic illuminations can be used for acquired imagedata without contributing to registration errors.

FIGS. 75A-75D are plots illustrating example data associated withregistration and position errors used in verifying the imageregistration processes and techniques described herein according to someexample implementations. As shown in FIGS. 75A-75B, plots for twodifferent samples of image data (e.g., “C1” and “D1”) illustrateregistration error counts (x-axis) as a function of the size of theregistration error (y-axis) in μm for high resolution images and lowresolution images. As shown in FIGS. 75A-75B, registration error countsare similar for high and low resolution images when using amonochromatic 12M sensor (e.g., a 3k sensor) with 0.4 magnification.

As shown in FIGS. 75C-75D, plots for two different samples of image data(e.g., “C1” and “D1”) illustrate registration vs. position errors counts(x-axis) as a function of the size of the error (y-axis) in μm for highresolution images and low resolution images. As shown in FIGS. 75C-75D,the majority of the errors are less than or equal to 1 pixel (e.g., ˜4.5μm) at 0.4 magnification for image data acquired at high resolution andlow resolution using the monochromatic 12M sensor.

FIG. 76 depicts an exemplary workflow 7600 for image and video captureby a sample handling apparatus described herein. The workflow 7600commences once substrates including a sample and an array are loaded inthe sample handling apparatus. A user can initiate the workflow bypressing a “start” button on the sample handling apparatus. In someembodiments, the initiation of the workflow 7600 can be programmaticallycontrolled by a computing device communicatively coupled to the samplehandling apparatus.

At 7610, after lid closure, a pre-sandwich image of the array slide iscaptured. Multiple images can be captured at this time. In someembodiments, images of the sample on the first substrate overlaid atopthe array on the second substrate are acquired at one or moreilluminations, such as illuminations including wavelengths associatedwith red, green, or blue light. In some embodiments, the images areacquired at one or more resolutions, such as a full resolution. Forexample, a full resolution can include a resolution associated with theas-designed resolution capabilities of the device acquiring the image,such as a 3000×3000 pixel resolution. In some embodiments, the imagesare acquired at one or more magnifications, such as 0.4 magnification. A0.4 magnification can be interpreted to indicate a 1 cm object can beimaged as a 0.4 cm object in the plane of the sensor acquiring theimage. In some embodiments, the images are acquired in a multilayer tagimage file format (TIFF). In some embodiments, the images are acquiredover a period of time, such as 3-5 seconds. Acquiring images during 7610can enable determination of serviceability of the sample handlingapparatus, and proper slide loading, as well as identification andrecording of pre-sandwich starting conditions. Following 7610, thesample handling apparatus commences to bring the first substrateincluding a sample together with the second substrate including thearray to initiate the start of the sandwiching process.

At 7620, the sandwich closure and sandwich alignment processes begins. Avideo of the sandwich closure process is acquired. In some embodiments,the video is acquired at a pre-determined frame rate, such as 30 framesper second (fps). In some embodiments, the video is acquired at one ormore illuminations, such as an illumination including a wavelengthassociated with a green light. In some embodiments, the video isacquired at one or more resolutions, such as 1000 pixel×1000 pixelresolution, which may be a resolution that is less than the as-designedresolution capabilities of the sensor acquiring the images. In someembodiments, the video is acquired in one or more video formats, such asan audio video interleave (AVI) format. The AVI formatted video file caninclude video data that is compressed using one or more compressionschemes, such as a compressed JPEG scheme. In some embodiments, thevideo is acquired for a period of time, such as 10 seconds. Acquiringvideo during 7620 can help determine the serviceability of the samplehandling apparatus.

At 7630, images of the aligned slides can be acquired. In someembodiments, images of the sample on the first substrate aligned atopthe array on the second substrate are acquired at one or moreilluminations, such as illuminations including wavelengths associatedwith red, green, or blue light. In some embodiments, the images areacquired at one or more resolutions, such as a full resolution asdescribed above in relation to 7610. In some embodiments, the images areacquired in a multilayer TIFF format. In some embodiments, the imagesare acquired over a period of time, such as 3-5 seconds. Acquiringimages during 7630 can enable determination of the output of the assaybeing performed.

At 7640, a video capturing the period of time in which the firstsubstrate including the sample is sandwiched with the second substrateincluding the array is acquired. The sandwich timer video can beassociated with a period of permeabilization performed during the assay.In some embodiments, the video is acquired at a pre-determined framerate, such as 0.5 fps. In some embodiments, the video is acquired at oneor more illuminations, such as an illumination including a wavelengthassociated with a green light. In some embodiments, the video isacquired at one or more resolutions, such as 1000 pixel×1000 pixelresolution as described above in relation to 7520. In some embodiments,the video is acquired in one or more video formats, such as an AVIformat. The AVI formatted video file can include video data that iscompressed using one or more compression schemes, such as a compressedJPEG scheme. In some embodiments, the video is acquired for a period oftime, such as ˜30 minutes. In some embodiments, the video is acquiredfor a period of time between 1-90 minutes. Acquiring video during 7640can help determine the serviceability of the sample handling apparatus.

At 7650, images can be acquired at the end of the sandwich process.Multiple images can be captured at this time. In some embodiments,images of the sample on the first substrate overlaid atop the array onthe second substrate are acquired at one or more illuminations, such asilluminations including wavelengths associated with red, green, or bluelight. In some embodiments, the images are acquired at one or moreresolutions, such as a full resolution as described above in relation to7610. In some embodiments, the images are acquired at one or moremagnifications, such as 0.4 magnification as described above in relationto 7610. In some embodiments, the images are acquired in a multilayerTIFF. In some embodiments, the images are acquired over a period oftime, such as 3-5 seconds. Acquiring images during 7650 can enabledetermination of serviceability of the sample handling apparatus, andidentification and recording sandwich conditions before opening thesandwich.

While workflows 1700, 1800, 2900, 3100, and 7600 are shown and describedwith respect to the sample handling apparatus 400, the workflows 1700,1800, 2900, 3100, and 7600 may also be performed with respect to thesample handling apparatus 1400, the sample handling apparatus 3000, oranother sample handling apparatus in accordance with the implementationsdescribed herein. In some embodiments, the processes 1900, 2300, 2500,2700, 2800, and 3000 may also be performed with respect to the samplehandling apparatus 1400, the sample handling apparatus 3000, or anothersample handling apparatus in accordance with the implementationsdescribed herein.

The spatialomic (e.g., spatial transcriptomic) processes and workflowsdescribed herein can be configured to display gene expressioninformation over high-resolution sample images. Barcoded locationswithin a reagent array can capture transcripts from a sample that is incontact with the array. The captured transcripts can be used insubsequent downstream processing. Determining the location of thebarcoded locations of the reagent array relative to the sample can beperformed using fiducial markers placed on a substrate on which thereagent array is located. The barcoded locations can be imaged with thesample to generate spatialomic (e.g., spatial transcriptomic) data forthe sample.

Generating image data suitable for spatialomic (e.g., spatialtranscriptomic) analysis can be affected by the relative alignment of asample with the barcoded regions of the reagent array. High-resolutionarrays for spatialomics (e.g., spatial transcriptomics) can requireresolution of the inferred barcoded locations overlaid atop ahigh-resolution sample image in order to properly associate the capturedtranscripts with the particular cell that the transcripts originatedfrom. The sample handling apparatus 400, 1400, and 3000 can beconfigured to perform the image registration processes and workflowsdescribed herein to provide a level of precision for aligning the sampleimage and the array image within +/−1-5 microns, +/−1-10 microns,+/−1-20 microns, or 1-30+/− microns.

One or more aspects or features of the subject matter described hereinmay be realized in digital electronic circuitry, integrated circuitry,specially designed ASICs, field programmable gate arrays (FPGAs)computer hardware, firmware, software, and/or combinations thereof.These various aspects or features may include implementation in one ormore computer programs that are executable and/or interpretable on aprogrammable system including at least one programmable processor, whichmay be special or general purpose, coupled to receive data andinstructions from, and to transmit data and instructions to, a storagesystem, at least one input device, and at least one output device. Theprogrammable system or computing system may include clients and servers.A client and server are generally remote from each other and typicallyinteract through a communication network. The relationship of client andserver arises by virtue of computer programs running on the respectivecomputers and having a client-server relationship to each other.

These computer programs, which may also be referred to as programs,software, software applications, applications, components, or code,include machine instructions for a programmable processor, and may beimplemented in a high-level procedural and/or object-orientedprogramming language, and/or in assembly/machine language. As usedherein, the term “machine-readable medium” refers to any computerprogram product, apparatus and/or device, such as for example magneticdiscs, optical disks, memory, and Programmable Logic Devices (PLDs),used to provide machine instructions and/or data to a programmableprocessor, including a machine-readable medium that receives machineinstructions as a machine-readable signal. The term “machine-readablesignal” refers to any signal used to provide machine instructions and/ordata to a programmable processor. The machine-readable medium may storesuch machine instructions non-transitorily, such as for example as woulda non-transient solid-state memory or a magnetic hard drive or anyequivalent storage medium. The machine-readable medium may alternativelyor additionally store such machine instructions in a transient manner,such as for example, as would a processor cache or other random accessmemory associated with one or more physical processor cores.

To provide for interaction with a user, one or more aspects or featuresof the subject matter described herein may be implemented on a computerhaving a display device, such as for example a cathode ray tube (CRT) ora liquid crystal display (LCD) or a light emitting diode (LED) monitorfor displaying information to the user and a keyboard and a pointingdevice, such as for example a mouse or a trackball, by which the usermay provide input to the computer. Other kinds of devices may be used toprovide for interaction with a user as well. For example, feedbackprovided to the user may be any form of sensory feedback, such as forexample visual feedback, auditory feedback, or tactile feedback; andinput from the user may be received in any form, including acoustic,speech, or tactile input. Other possible input devices include touchscreens or other touch-sensitive devices such as single or multi-pointresistive or capacitive track pads, voice recognition hardware andsoftware, optical scanners, optical pointers, digital image capturedevices and associated interpretation software, and the like.

In the descriptions above and in the claims, phrases such as “at leastone of” or “one or more of” may occur followed by a conjunctive list ofelements or features. The term “and/or” may also occur in a list of twoor more elements or features. Unless otherwise implicitly or explicitlycontradicted by the context in which it used, such a phrase is intendedto mean any of the listed elements or features individually or any ofthe recited elements or features in combination with any of the otherrecited elements or features. For example, the phrases “at least one ofA and B;” “one or more of A and B;” and “A and/or B” are each intendedto mean “A alone, B alone, or A and B together.” A similarinterpretation is also intended for lists including three or more items.For example, the phrases “at least one of A, B, and C;” “one or more ofA, B, and C;” and “A, B, and/or C” are each intended to mean “A alone, Balone, C alone, A and B together, A and C together, B and C together, orA and B and C together.” Use of the term “based on,” above and in theclaims is intended to mean, “based at least in part on,” such that anunrecited feature or element is also permissible.

The subject matter described herein may be embodied in systems,apparatus, methods, and/or articles depending on the desiredconfiguration. The implementations set forth in the foregoingdescription do not represent all implementations consistent with thesubject matter described herein. Instead, they are merely some examplesconsistent with aspects related to the described subject matter.Although a few variations have been described in detail above, othermodifications or additions are possible. In particular, further featuresand/or variations may be provided in addition to those set forth herein.For example, the implementations described above may be directed tovarious combinations and subcombinations of the disclosed featuresand/or combinations and subcombinations of several further featuresdisclosed above. In addition, the logic flows depicted in theaccompanying figures and/or described herein do not necessarily requirethe particular order shown, or sequential order, to achieve desirableresults. Other implementations may be within the scope of the followingclaims.

1. A method for aligning a sample to an array, the method comprising:receiving, by a data processor, sample image data comprising a sampleimage of the sample, the sample image having a first resolution;receiving, by the data processor, array image data comprising an arrayimage comprising an overlay of an array with the sample, and an arrayfiducial, the array image having a second resolution lower than thefirst resolution of the sample image; registering, by the dataprocessor, the sample image to the array image by aligning the sampleimage and the array image; generating, by the data processor, an alignedimage based on the registering, the aligned image comprising an overlayof the sample image with the array; and providing, by the dataprocessor, the aligned image.
 2. The method claim 1, wherein the sampleimage data is received from a user or from a computing device remotefrom the data processor.
 3. The method of claim 1, wherein the alignedimage further comprises the array fiducial aligned with the sample. 4.The method of claim 1, wherein the sample image further comprises asample fiducial delineating a sample area into which the sample isplaced.
 5. The method of claim 1, wherein the sample image is of thesample on a first substrate.
 6. The method of claim 1, wherein thesample is located on a first substrate and the array is located on asecond substrate.
 7. The method of claim 1, wherein the array and thearray fiducial are located on a first side of a second substrate.
 8. Themethod claim 7, wherein the array fiducial is located on the secondsubstrate adjacent to, within, or distanced from a reagent configured onthe second substrate.
 9. The method of claim 1, wherein the array imageincludes a portion of the array overlaid atop a portion of the samplebased on a location of the array fiducial.
 10. The method of claim 1,wherein the sample image comprises a plurality of sample portion images,each sample portion image associated with a portion of the sample,wherein a size of each sample portion image is less than a size of asingle field of view of the sample image.
 11. The method of claim 10,wherein registering the sample image to the array image furthercomprises cropping, by the data processor, the sample image to determinethe plurality of sample portion images; and registering one or moresample portion images in the sample image to a corresponding portion ofthe sample in the array image.
 12. The method of claim 11, whereinregistering the one or more sample portion images in the sample image tothe corresponding portion of the sample in the array image is performedafter registering the sample image to the array image.
 13. The method ofclaim 1, wherein the array image comprises a plurality of array portionimages, each array portion image associated with a portion of the array,wherein a size of each array portion image is less than a size of asingle field of view of the array image.
 14. The method of claim 13,wherein the registering further comprises determining, by the dataprocessor, the plurality of array portion images in the array image; andregistering, by the data processor, one or more array portion images inthe array image to a corresponding portion of the sample in the sampleimage.
 15. A system for aligning a sample to an array, the systemcomprising: a sample holder comprising a first retaining mechanismconfigured to retain a first substrate received within the firstretaining mechanism, the first substrate comprising a sample, and asecond retaining mechanism configured to retain a second substratereceived within the second retaining mechanism, the second substratecomprising an array, the sample holder configured to adjust a locationof the first substrate relative to the second substrate to cause all ora portion of the sample to be aligned with the array; a microscopeoperatively coupled to the sample holder, the microscope configured toview the first substrate and the second substrate within the sampleholder; and acquire image data associated with the sample and/or thearray; and a first computing device communicatively coupled to themicroscope and to the sample holder, the computing device comprising adisplay, a data processor, and a non-transitory computer readablestorage medium storing computer readable and executable instructions,which when executed cause the data processor to perform operationscomprising receiving sample image data comprising a sample image of thesample, the sample image having a first resolution; receiving arrayimage data comprising an array image having a second resolution lowerthan the first resolution of the sample image, the array imagecomprising the array and an array fiducial overlaid atop the sample;registering the sample image to the array image by aligning the sampleimage and the array image; generating an aligned image based on theregistering, the aligned image comprising the sample aligned with thearray; and providing the aligned image.
 16. The system of claim 15,wherein the sample image data is received from a user or from acomputing device remote from the data processor.
 17. The system of claim15, wherein the aligned image further comprises the array fiducialaligned with the sample.
 18. The system of claim 15, wherein the sampleimage further comprises a sample fiducial delineating a sample area intowhich the sample is placed on the first substrate.
 19. The system ofclaim 15, wherein the sample image is of the sample on the firstsubstrate.
 20. The system of claim 15, wherein the array fiducial islocated on the second substrate adjacent to, within, or distanced from areagent configured on the second substrate.
 21. The system of claim 15,wherein the sample image comprises a plurality of sample portion images,each sample portion image associated with a portion of the sample,wherein a size of each sample portion image is less than a size of asingle field of view of the sample image.
 22. The system of claim 21,wherein the registering further comprises cropping, by the dataprocessor, the sample image to determine the plurality of sample portionimages; and registering one or more sample portion images in the sampleimage to a corresponding portion of the sample in the array image. 23.The system of claim 15, wherein the array image comprises a plurality ofarray portion images, each array portion image associated with a portionof the array, wherein a size of each array portion image is less than asize of a single field of view of the array image.
 24. The system ofclaim 23, wherein the registering further comprises determining theplurality of array portion images in the array image; and registeringone or more array portion images in the array image to a correspondingportion of the sample in the sample image.